轧辊热处理过程中若干调度问题的启发式算法研究
|
摘要
轧辊行业属于钢铁制造行业的上层企业。轧辊生产工艺流程由造型、冶炼、浇铸、热处理、机加工等诸多工艺组成。其中,由于热处理工艺加工周期长、生产成本高,使其在轧辊生产工艺流程中处于突出重要的地位。近年来,随着钢铁行业的迅速发展,轧辊产品的需求量不断提高,轧辊企业的生产订单不断增加,造成热处理工艺中的加热炉数量相对减少,进而使得热处理过程成为整个生产工艺流程的瓶颈。因此,在现有资源条件下,如何提高热处理过程中加热炉的利用率,提高轧辊企业的生产管理水平,降低生产成本,提升企业竞争力具有十分重要的意义。
本文以国内某机械轧辊企业生产与信息管理开发项目为依托,通过对企业的实地调研,并应用生产管理及系统工程的相关理论,在建立轧辊生产计划与调度体系构架的基础上,针对轧辊生产热处理过程中若干优化调度问题进行了研究。该研究是国家“973”项目(2009CB320601)和国家杰出青年基金项目(70625001)的重要组成部分。论文的主要研究工作包括以下五个方面：
(1)对轧辊生产计划与调度过程进行了研究。通过分析轧辊生产工艺流程的特点以及实际生产中生产管理方法存在的问题,应用生产管理的相关理论知识,建立了轧辊生产计划与调度体系构架,并在该体系构架的基础上,建立了轧辊生产计划与调度系统功能结构图,为后续热处理过程中若干优化调度问题的研究奠定了基础；
(2)针对面向热处理过程的辊坯组批和批次调度的单阶段优化调度问题进行了研究,该问题被归结为具有组批的并行机调度问题。建立了问题的数学模型,提出了三种辊坯组批启发式和三种批次调度启发式,并将其有效地结合对模型进行求解,通过对实验结果比较与分析,验证了算法的有效性,并针对该问题给出了相应的最佳求解方法；
(3)针对面向热处理过程的批次指派和批次调度的单阶段优化调度问题进行了研究,该问题属于具有指派的并行机调度问题。针对问题中高温炉容积不同这一特点,分别对确定性指派和非确定性指派并行机调度问题提出了相应的指派启发式算法,并结合研究内容(2)中的批次调度启发式对建立的数学模型进行求解,在分析实验结果的基础上,我们得知应用调整最短加工时间辊坯批次的非确定性指派启发式算法得到的调度结果最优；
(4)针对面向热处理过程的辊坯组批、批次指派及批次调度的单阶段集成决策问题进行了研究。建立了问题的数学模型,针对轧辊热处理实际生产中两种不同容积的高温炉数量相等的特点,提出了一种交替组批启发式算法,在批次调度阶段提出了一种采用顺序编码方式的遗传算法。通过实验结果的比较分析,验证了算法的可行性和有效性,为企业决策者合理安排生产提供依据；
(5)针对面向热处理过程的加热炉容积相同情况下的多阶段优化调度问题进行了研究,该问题被归结为无等待混合流水车间调度问题。建立了问题的数学模型,针对辊坯批次在任意两个阶段间不允许等待这一特点,提出了一种分阶段无等待算法,并将该算法与离散粒子群优化算法相结合对模型求解,为了保证算法中的粒子始终保持顺序编码方式,提出了一种可行解调整策略。最后通过实验结果的比较分析,验证了算法的有效性,并给出了具有实际参考价值的设备改进策略,对生产决策者合理安排生产具有一定指导意义。
The mill roll industry is an upper-layer enterprise of the iron and steel manufacturing industry. The mill roll process flow is composed of the smelting, the molding, the casting, the heat treatment and the machining crafts and so on, in which the heat treatment plays a special important role because of the long processing cycle and high production costs in the mill roll process flow. In recent years, along with the rapid development of the iron and steel industry, the demand quantity of mill roll products and the production order quantity of the mill roll enterprise are increased continuously, which will lead to a reduction relatively for the heating quantity of the heat treatment. And then the heat treatment process becomes a bottleneck of the whole mill roll production flow. Therefore, under the condition of the existing resources, how to improve the utilization ratio of heating furnace in the heat treatment process, improve the production management level, and reduce production costs is very important to increase competitiveness of enterprises.
In this dissertation, based on a production and information management development project of the machinery and mill roll enterprise in mainland China, and through investigating the actual situation of this enterprise and applying the relevant theories of the production management and the systems engineering, and then on the basis of establishing the system architecture of the mill roll production planning and scheduling, we establish the system function diagram of the mill roll production planning and scheduling. It lays a foundation for the following study on some optimization and scheduling problems of the mill roll heat treatment process. At the same time, it is a constituent part of the national '985'project (2009CB320601) and the'National Natural Science Funds for Distinguished Young Scholar project'(70625001).
To sum up, this dissertation focuses on the five key problems:
(1) We discuss the process of the mill roll production planning and scheduling. On the basis of analyzing the characteristics of the mill roll production flow and some production management problems in the actual production, and applying the relevant theory of the production management, the system architecture of the mill roll production planning and scheduling is built. This system architecture includes five function modules:data management, production contract making, master production planning making, monthly production planning and job scheduling making.
(2) We study a single-stage optimization scheduling problem with the rough mill roll batching and the batch scheduling for the heat treatment process. This problem can be seen as a parallel machines scheduling problem with batch loading. On this basis, we tried to combine three rough mill roll batching heuristics with three batch scheduling heuristics to solve the built mathematical model. In the simulation experiment, the effectiveness of the algorithm is demonstrated by the comparisons and analyses of results. At last, the optimization solving method is given for this problem.
(3) We discuss a single-stage optimization scheduling problem with the batch assignment and the batch scheduling for the heat treatment process. This problem belongs to a parallel machines scheduling problem with assignment. With regard to the high temperature furnaces with different volumes, we present different assignment heuristics for both the parallel machines scheduling with specified assignment and the parallel machines scheduling with unspecified assignment respectively. We tried to combine all assignment heuristics with batch scheduling heuristics of (2) to solve the built mathematical model. The last simulation experiments show that the optimization scheduling results of the adjusting roller batches of shortest processing time with unspecified assignment heuristics are superior to those of other assignment heuristics.
(4) We discuss a single-stage integrated decision-making problem with the rough mill roll batching, the batch assignment and the batch scheduling for the heat treatment process. In this problem, because the number of high temperature furnaces is equal to that of low temperature furnaces, we present the alternative batching assignment heuristics during the batch assignment. Furthermore, we develop a genetic algorithm with the sequence encoding during the batch scheduling. At last, the effectiveness of the algorithm is demonstrated by the comparisons and analyses of results, and some methods are given for the policy-maker to arrange production reasonably.
(5) We discuss a multi-stage optimization scheduling problem with the same volume of heating furnaces for the heat treatment process. This problem can be seen as a no-wait hybrid flow shop scheduling problem. According to the no-wait characteristic between two sequential operations of the batch, the no-wait algorithm in stages is designed. Combined with the no-wait algorithm in stages, a discrete particle swarm optimization algorithm is developed to solve the integer-programming model. In order to assure the particle encoding still keep the sequential encoding we present a feasible solution adjustment method. At last, the effectiveness of the algorithm is demonstrated by the comparisons and analyses of results, and the equipment reformation strategies of actual reference value are given as well which is beneficial for the policy-maker to arrange production reasonably.
本文以国内某机械轧辊企业生产与信息管理开发项目为依托,通过对企业的实地调研,并应用生产管理及系统工程的相关理论,在建立轧辊生产计划与调度体系构架的基础上,针对轧辊生产热处理过程中若干优化调度问题进行了研究。该研究是国家“973”项目(2009CB320601)和国家杰出青年基金项目(70625001)的重要组成部分。论文的主要研究工作包括以下五个方面：
(1)对轧辊生产计划与调度过程进行了研究。通过分析轧辊生产工艺流程的特点以及实际生产中生产管理方法存在的问题,应用生产管理的相关理论知识,建立了轧辊生产计划与调度体系构架,并在该体系构架的基础上,建立了轧辊生产计划与调度系统功能结构图,为后续热处理过程中若干优化调度问题的研究奠定了基础；
(2)针对面向热处理过程的辊坯组批和批次调度的单阶段优化调度问题进行了研究,该问题被归结为具有组批的并行机调度问题。建立了问题的数学模型,提出了三种辊坯组批启发式和三种批次调度启发式,并将其有效地结合对模型进行求解,通过对实验结果比较与分析,验证了算法的有效性,并针对该问题给出了相应的最佳求解方法；
(3)针对面向热处理过程的批次指派和批次调度的单阶段优化调度问题进行了研究,该问题属于具有指派的并行机调度问题。针对问题中高温炉容积不同这一特点,分别对确定性指派和非确定性指派并行机调度问题提出了相应的指派启发式算法,并结合研究内容(2)中的批次调度启发式对建立的数学模型进行求解,在分析实验结果的基础上,我们得知应用调整最短加工时间辊坯批次的非确定性指派启发式算法得到的调度结果最优；
(4)针对面向热处理过程的辊坯组批、批次指派及批次调度的单阶段集成决策问题进行了研究。建立了问题的数学模型,针对轧辊热处理实际生产中两种不同容积的高温炉数量相等的特点,提出了一种交替组批启发式算法,在批次调度阶段提出了一种采用顺序编码方式的遗传算法。通过实验结果的比较分析,验证了算法的可行性和有效性,为企业决策者合理安排生产提供依据；
(5)针对面向热处理过程的加热炉容积相同情况下的多阶段优化调度问题进行了研究,该问题被归结为无等待混合流水车间调度问题。建立了问题的数学模型,针对辊坯批次在任意两个阶段间不允许等待这一特点,提出了一种分阶段无等待算法,并将该算法与离散粒子群优化算法相结合对模型求解,为了保证算法中的粒子始终保持顺序编码方式,提出了一种可行解调整策略。最后通过实验结果的比较分析,验证了算法的有效性,并给出了具有实际参考价值的设备改进策略,对生产决策者合理安排生产具有一定指导意义。
The mill roll industry is an upper-layer enterprise of the iron and steel manufacturing industry. The mill roll process flow is composed of the smelting, the molding, the casting, the heat treatment and the machining crafts and so on, in which the heat treatment plays a special important role because of the long processing cycle and high production costs in the mill roll process flow. In recent years, along with the rapid development of the iron and steel industry, the demand quantity of mill roll products and the production order quantity of the mill roll enterprise are increased continuously, which will lead to a reduction relatively for the heating quantity of the heat treatment. And then the heat treatment process becomes a bottleneck of the whole mill roll production flow. Therefore, under the condition of the existing resources, how to improve the utilization ratio of heating furnace in the heat treatment process, improve the production management level, and reduce production costs is very important to increase competitiveness of enterprises.
In this dissertation, based on a production and information management development project of the machinery and mill roll enterprise in mainland China, and through investigating the actual situation of this enterprise and applying the relevant theories of the production management and the systems engineering, and then on the basis of establishing the system architecture of the mill roll production planning and scheduling, we establish the system function diagram of the mill roll production planning and scheduling. It lays a foundation for the following study on some optimization and scheduling problems of the mill roll heat treatment process. At the same time, it is a constituent part of the national '985'project (2009CB320601) and the'National Natural Science Funds for Distinguished Young Scholar project'(70625001).
To sum up, this dissertation focuses on the five key problems:
(1) We discuss the process of the mill roll production planning and scheduling. On the basis of analyzing the characteristics of the mill roll production flow and some production management problems in the actual production, and applying the relevant theory of the production management, the system architecture of the mill roll production planning and scheduling is built. This system architecture includes five function modules:data management, production contract making, master production planning making, monthly production planning and job scheduling making.
(2) We study a single-stage optimization scheduling problem with the rough mill roll batching and the batch scheduling for the heat treatment process. This problem can be seen as a parallel machines scheduling problem with batch loading. On this basis, we tried to combine three rough mill roll batching heuristics with three batch scheduling heuristics to solve the built mathematical model. In the simulation experiment, the effectiveness of the algorithm is demonstrated by the comparisons and analyses of results. At last, the optimization solving method is given for this problem.
(3) We discuss a single-stage optimization scheduling problem with the batch assignment and the batch scheduling for the heat treatment process. This problem belongs to a parallel machines scheduling problem with assignment. With regard to the high temperature furnaces with different volumes, we present different assignment heuristics for both the parallel machines scheduling with specified assignment and the parallel machines scheduling with unspecified assignment respectively. We tried to combine all assignment heuristics with batch scheduling heuristics of (2) to solve the built mathematical model. The last simulation experiments show that the optimization scheduling results of the adjusting roller batches of shortest processing time with unspecified assignment heuristics are superior to those of other assignment heuristics.
(4) We discuss a single-stage integrated decision-making problem with the rough mill roll batching, the batch assignment and the batch scheduling for the heat treatment process. In this problem, because the number of high temperature furnaces is equal to that of low temperature furnaces, we present the alternative batching assignment heuristics during the batch assignment. Furthermore, we develop a genetic algorithm with the sequence encoding during the batch scheduling. At last, the effectiveness of the algorithm is demonstrated by the comparisons and analyses of results, and some methods are given for the policy-maker to arrange production reasonably.
(5) We discuss a multi-stage optimization scheduling problem with the same volume of heating furnaces for the heat treatment process. This problem can be seen as a no-wait hybrid flow shop scheduling problem. According to the no-wait characteristic between two sequential operations of the batch, the no-wait algorithm in stages is designed. Combined with the no-wait algorithm in stages, a discrete particle swarm optimization algorithm is developed to solve the integer-programming model. In order to assure the particle encoding still keep the sequential encoding we present a feasible solution adjustment method. At last, the effectiveness of the algorithm is demonstrated by the comparisons and analyses of results, and the equipment reformation strategies of actual reference value are given as well which is beneficial for the policy-maker to arrange production reasonably.
引文
1.金庆珍.山东钢铁工业“十一五”科技发展研究[J].山东冶金,2005,6：1-12.
2.高慧敏,曾建潮.钢铁生产调度智能优化与应用[M].北京：冶金工业出版社,2006,1-10.
3.刘均贤,韩静涛.冶金工业的发展及其对冶金轧辊的需求[J],大型铸锻件,2006,4：41-44.
4.俞誓达,陈菡.我国轧辊业现状及发展中应重视的问题[J],钢铁,2007,42(7)：1-6.
5. 贾建平.中国轧辊制造业技术现状与发展趋势(上)[J],中国钢铁业,2008,9：24-27.
6.2008-2010年中国轧辊行业研究与市场预测分析报告[R],中国行业研究报告网,2008,2-29.
7.吴素霞.计算机集成制造系统_CIMS_及其在我国的发展现状[J].科技与产业,2005,5(5)：62-64.
8.贾建平.中国轧辊制造业技术现状与发展趋势(下)[J],中国钢铁业,2008,10：27-31.
9. 薛灵虎.推进我国轧辊行业的技术进步[J],中国冶金,2002,61(6)：35-43.
10.徐继山.铸造合金半钢轧辊热处理工艺探讨[J],金属加工,2008,21：32-34.
11.金以慧,王诗亦,王桂增.过程控制的发展与展望[J].控制理论与应用,1997,14(2)：145-151.
12.徐俊刚,戴国忠,王宏安.生产调度理论和方法研究综述[J].计算机研究和发展,2004,41(2)：257-267.
13.蒋圣平,邹益仁,梁刚.钢铁企业CIMS下生产计划的研究[J],冶金自动化,2003,27(6)：1-6.
14.杨智茗,张洪伟,赵立.ERP生产规划系统的探索和实现[J],计算机工程与设计,2003,24(2)：46-49.
15.李锦飞,马汉武,陈纪南.生产管理与调度[M].北京：化工工业出版社,2005,77-80.
16.王丽莉,张凤荣.生产计划与控制[M].北京：机械工业出版社,2006,56-58.
17. Jorma K, Ovako O. The short term (1-15 months) planning and control of a steel plant [J]. Engineering and Process Economics,1979,4(2):235-243.
18. Rudi R. Developing a practical planning system for a steel business [J]. Long Range Planning, April 1986,19(2):90-100.
19. Tang L X. A review of planning and scheduling systems and methods for integrated steel production [J]. European Journal of Operational Research,2001,133(1):1-20.
20. Gershon M. Heuristic approaches for mine planning and production scheduling [J]. International Journal of Mining and Geological Engineering.1987,5(1):1-13.
21. Fabian T. Blast furnace production planning-a linear programming example [J]. Management Science,1967,14(2):1-27.
22.李建祥,唐立新,王梦光.钢铁企业的多品种多时段高炉生产计划问题研究[J].系统工程学报,2003,18(5)：438-446.
23.陈安福,罗运清.重钢中板生产计划优化及其对生产的影响[J].轧钢,2009,26(4)：52-54.
24.郑秉霖,胡琨元,常春光.一体化钢铁生产计划系统的研究现状与展望[J].控制工程,2003,(1)：6-10.
25. Liu Shixin, Tang Jiafu, Song Jianhai. Order-planning model and algorithm for manufacturing steel sheets [J]. International Journal of Production Economics,2006, 100(1):30-43.
26. Kumar A S, Srinivas, Tiwari M K. Modelling the slab stack shuffling problem in developing steel rolling schedules and its solution using improved Parallel Genetic Algorithms [J].International Journal of Production Economics,2004,91 (2):135-147.
27.唐立新CIMS下生产批量计划理论及其应用[M].北京：科学出版社,1998.
28. Ouelhadj D, Petrovic S, Cowling P I, et al.Inter-agent cooperation and communication for agent-based robust dynamic scheduling insteel production [J]. Advanced Engineering Informatics,2004,18 (3):161-172.
29. Denby B, SchofieldD, Bradford S. Neuralnetwork applications inmining engineering [R]. Nottingham:University of Nottingham,1991.
30. HafeezK, GriffithsM, Griffiths J, et al. Systems design of a two-echelon steel industry supply chain [J]. International Journal of Production Economics,1996,45(1-3): 121-130.
31. Bicheno J, Holweg M, Niessmann J. Constraint batch sizing in a lean environment [J]. International Journal of Production Economics,2001,73(2):41-49.
32. Taylor D H. Measurement and analysis of demand amplification across the supply chain [J]. International Journal of Logistics management,1999,10 (2):55-70.
33.李建祥,唐立新.钢铁供应链生产计划与调度研究综述[J].控制工程,2010,17(1)：123-126.
34. Goutam D, Robert F. A survey of mathematical programming applications in integrated steel plants [J]. IBM J RES DE-VELOPS,1997,58 (2):123-132.
35. Bellabdaoui A, Teghem J. A mixed-integer linear programming model for the continuous casting planning [J]. International Journal of Production Economics,2004, 124(3):1-11.
36. Peter C. A flexible decision support system for steel hot rolling mill scheduling [J]. Computers & Industrial Engineering,2003,45 (2):307-321.
37. Tang L X, Liu J Y, Rong A Y, et al. A multiple traveling salesman problem model for hot rolling scheduling in Shanghai Baoshan Iron & Steel Complex [J]. European Journal of Operational Research,2000,124 (2):267-282.
38. Bowers M R, Kaplan L A, Hooker T L. A two-phase model for Planning the production of aluminum ingot [J]. European Journal of Operational Research,1995,81(1): 105-114.
39.彭志刚,吴广宇,杨艳丽等.一机两流的连铸生产计划模型与算法[J].东北大学学报(自然科学版),2000,3：244-246.
40.史海波,马玉林,刘爱国.冶金冷轧薄板企业生产计划调度体系结构及方法研究[J].信息与控制,2004,2：31-35.
41. Tang L X, Liu J Y, Rong A Y, et al. A mathematical programming model for scheduling steel making-continuous casting production [J]. European Journal of Operational Research,2000, (2):423-435.
42. Narchal R M. A simulation model for corporate planning in a steel plant [J]. European Journal of Operational Research,1988,34(3):282-296.
43.李耀华,宁树实,王伟.基于准时制的轧钢厂生产计划模型及算法[J].控制工程,2004,2：321-324.
44.蒋圣平,邹益仁.钢铁企业年度生产计划的研究[J].控制与决策,2004,6：695-698.
45. Fox M S. Constraint-guided scheduling-A short history of research at CMU [J]. Computer in Industry,1990,14:79-88.
46. Rodammer F A, Whit K P. A recent survey of production scheduling [J]. IEEE Transactions on System Man and Cybernetic,1988,18(6):841-851.
47.王万良,吴启迪.生产调度智能算法及其应用[M].北京：科学出版社,2007,8-16.
48.柳毅.企业生产调度的智能优化方法[M].北京：人民邮电出版社,2008,5-10.
49. Huang X, Wang J B, Wang L Y, et al. Single machine scheduling with time-dependent deterioration and exponential learning effect [J]. Computers & Industrial Engineering, 2010,58(1):58-63.
50. Kuo W H, Yang D L. Single machine scheduling with past-sequence-dependent setup times and learning effects [J].Information Processing Letters,2007,102(1):22-26.
51. Jorge M S, Valente. Beam search heuristics for the single machine early/tardy scheduling problem with no machine idle time [J]. Computers & Industrial Engineering, 2008,55(3):663-675.
52.刘振刚,王道平,金峰.带组换装时间的单机调度问题[J].北京科技大学学报,2009,31(10)：1347-1350.
53. Adibi M A, Zandieh M, Amiri M. Multi-objective scheduling of dynamic job shop using variable neighborhood search [J]. Expert Systems with Applications,2010,37(1): 282-287.
54. Fawaz S A, Sotskov Y N, Allahverdi A, et al. Using mixed graph coloring to minimize total completion time in job shop scheduling [J]. Applied Mathematics and Computation,2006,182(2):1137-1148.
55. Guo Z X, Wong W K, Leung S Y, et al. Mathematical model and genetic optimization for the job shop scheduling problem in a mixed- and multi-product assembly environment:A case study based on the apparel industry [J]. Computers & Industrial Engineering,2006,50(3):202-219.
56. Zhang C Y, Li P G, Rao Y Q. A very fast TS/SA algorithm for the job shop scheduling problem [J]. Computers & Operations Research,2008,35(1):282-294.
57.唐立新,杨自厚,王梦光.基于准时制的炼钢-连铸生产调度问题研究[J].自动化学报,1998,24(1)：9-14.
58.方宇炜,韩曾晋.炼钢连铸过程的Petri网实时调度模型[J].清华大学学报,1999,39(1)：79-82.
59.孙福权,唐立新,郑秉霖.炼钢连铸生产调度专家系统[J].冶金自动化,1998,6：31-33.
60.李锦英,唐立新,王梦光.基于可视化虚拟现实技术的炼钢、连铸生产调度系统[J].冶金自动化,1999,4：14-17.
61.李霄峰,徐立云,邵惠鹤,任德祥.炼钢连铸系统的动态调度模型和启发式调度算法[J].上海交通大学学报,2001,35(11)：1658-1662.
62. Numao M, Morishita S. Cooperative scheduling and its application to steelmaking process [J]. IEEE Transaction on Industrial Electronics,1991,38(2):150-155.
63. Lally B, Biegler L. Henein H. A model for sequencing a continuous casting operation to minimize costs [J]. Iron and Steelmaker,1987,14(10):63-70.
64. Lee H S, Murthy S S, Haider S W, et al. Primary production scheduling at steelmaking industries [J]. IBM Journal of Research and Development,1996,40(2):231-252.
65. Meil D, Lee H S. Scheduling steel production on two twin-strand casters [C]. Proceedings of the International Manufacturing Productivity Symposium, NY,1993.
66. Takahashi T. Scheduling for steel making process using mathematical programming method [J]. Kobe Steel Engineering Reports,1990,40(3):29-32.
67. Neuwirth J. A production scheduling system at the stahlline GMBH [C]. International Conference on Computerized Production Control in Steel Plant, Korea,1993.
68. Tang L X, Yang Z H, Wang M G. Optimal model and algorithms for charge plan in steel-making and continuous casting production [J]. Journal of Northeastern University, 1996,17(4):440-445.
69. Tang L X, Yang Z H, Wang M G. Optimal model and algorithms for CAST plan in steel making and continuous casting production [J]. Journal of Northeastern University,1996, 17(5):554-558.
70. Tang L X, Yang Z H, Wang M G. Optimal model and algorithms for casting plan with unknown number of CAST in the steel making and continuous casting production [J]. Journal of Iron and Steel,1997,32(10):19-21.
71.徐心和,陈雄,郭念忠,谭金东.炼钢-连铸-热轧一体化管理[J].冶金自动化,1997,3：1-4.
72.唐立新,杨自厚,沈宏宇,胡国奋.炼钢-连铸-热轧集成批量计划因素分析[J].钢铁,2000,35(5)：74-76.
73.孙福权,郑秉霖,唐立新,崔建江,冯少丽.炼钢-连铸-热轧一体化集成调度管理[J].钢铁,1998,33(12)：71-75.
74.孙福权,郑秉霖,崔建江,汪定伟,刘新胜.炼钢-热轧一体化管理的生产计划编制问题研究[J].自动化学报,2000,26(3)：409-413.
75.张彩霞,石亦平,贺城江,韩静涛,贺毓辛.冶铸轧一体化生产调度方法的探讨[J].钢铁,2000,35(2)：74-77.
76.朱宝琳,于海斌.炼钢-连铸-热轧生产调度模型及算法研究[J].计算机集成制造系统,2003,9(1)：33-36.
77.于银俊,易先堂,王尚勤.运用微机管理优化连铸连轧生产调度计划方法的探讨[J].冶金信息导刊,2001,5：24-26.
78.彭其春,包燕平,田乃媛,王德城.一体化生产管理系统炼钢计划子系统设计[J].北京科技大学学报,2002,24(1)：25-28.
79. Peter C, Rezig W. Integrated of continuous caster and hot strip mill planning for steel production [J]. Journal of Scheduling,2000,36(3):185-208.
80. Tamura R, Nagai N, Nakagawa Y, et al. Functionally partitioned scheduling system equipped with two-stage scheduling algorithm in steel sheet manufacturing [J]. Instruments and Automatic Control,1995,8(10):592-601.
81.王芸凤.智能生产调度方法的研究与应用[D].合肥：合肥工业大学,2005.
82.玄光男,程润伟.遗传算法与工程设计[M].汪定伟,唐加福,黄敏译.北京：科学出版社,2000,171-173.
83. McNaughton R. Scheduling with deadlines and loss functions [J]. Management Science, 1959,6(1):1-12.
84. Garey M, Johnson D. Strong NP-completeness results:motivation, examples and implications [J]. Journal of ACM,1978,25(9):499-508.
85. Bruno L, Coffman J, Sethi R. Scheduling independent tasks to reduce mean finishing time [J]. Communications on ACM,1974,17(6):382-387.
86. Li C, Cheng T. The parallel machine min-max weighted absolute lateness scheduling problem [J]. Naval Research Logistics,1993,41(3):33-46.
87. Chu C B, Yalaoui F. Parallel machine scheduling to minimize total tardiness [J]. International Journal of Production Economics,2002,76(3):265-279.
88. Kim Y-D, Shim S-O. Scheduling on parallel identical machines to minimize total tardiness [J]. European Journal of Operational Research,2007,177(1):135-146.
89. Kim Y-D, Shim S-O. A branch and bound algorithm for an identical parallel machine scheduling problem with a job splitting property [J]. Computers & Operations Research, 2008,35(3):863-875
90. Dogramaci A, Surkis J. Evaluation of a heuristics for scheduling independent jobs on parallel identical processors [J]. Management Science,1979,25(4):1208-1216.
91. Ho J C, Chang Y-L. Heuristics for minimizing mean tardiness for m parallel machines [J]. Naval Research Logistics,1991,38(5):367-381.
92. Alidaee B, Rosa D. Scheduling parallel machines to minimize total weighted and un-weighted tardiness [J]. Computers & Operations Research,1997,24(8):775-788.
93. Biskup D, Herrmann J, Gupta J N D. Scheduling identical parallel machines to minimize total tardiness [J]. International Journal of Production Economics,2008, 115(1):134-142.
94. Xu D H, Cheng Z, Yin Y, Li H X. Makespan minimization for two parallel machines scheduling with a periodic availability constraint [J]. Computers & Operations Research,2009,36(6):1809-1812.
95. Vinicius A, Armentano, Moacir F. Minimizing total tardiness in parallel machine scheduling with setup times:An adaptive memory-based GRASP approach [J]. European Journal of Operational Research,2007,183(1):100-114.
96. Xu D H, Sun K B, Li H X. Parallel machine scheduling with almost periodic maintenance and non-preemptive jobs to minimize makespan [J]. Computers & Operations Research,2008,35(4):1344-1349.
97. Kim E-S, Sung C-S, Lee I-S. Scheduling of parallel machines to minimize total completion time subject to s-precedence constraints [J]. Computers & Operations Research,2009,36(3):698-710.
98. Wang X L, Cheng T C E. Heuristics for parallel-machine scheduling with job class setups and delivery to multiple customers [J]. International Journal of Production Economics,2009,119(1):199-206.
99.时维国,宋存利,黄明.基于启发式算法的并行多机调度问题研究[J].大连铁道学院学报,2003,24(4)：55-58.
100. Mateus R P, Mateus G R, Ravetti M G. A non-delayed relax-and-cut algorithm for scheduling problems with parallel machines, due dates and sequence-dependent setup times [J]. Computers & Operations Research,2010,37(5):938-949.
101.宁凝,钱省三,孟志雷.带有工艺约束的并行多机调度策略[J].工业工程,2008,11(2)：62-65.
102. Cheng R, Gen M, Tozawa T. Minmax earliness/tardiness scheduling in identical parallel machine system using genetic algorithms [J]. Computers & Industrial Engineering,1995,29(1-4):513-517.
103.何敬东,黄向,严太山.并行机调度遗传算法研究[J].大众科技,2008,6：54-56.
104.朱长武,戴上平,刘智.并行遗传算法在并行多机调度中的应用[J].微计算机信息,2007,23(2-3)：200-201.
105.吴昊,程锦松.用并行遗传算法解决带约束并行多机调度问题[J].微机发展,2001,1：19-22.
106.何桂霞,高家全,王雨顺.特殊工艺约束并行多机双目标调度问题的研究[J].计算机工程与应用,2008,44(32)：197-200.
107.周辉仁.递阶遗传算法理论及其应用研究[D].天津大学,2008.
108.周辉仁,郑丕鄂,王海龙.基于递阶遗传算法的最小加权完土时间并行机调度[J].系统仿真学报,2008,20(13)：3510-3513.
109.刘民,吴澄,戴元顺.最小化拖期任务数并行机调度问题的一种基于知识的遗传算法[J].电子学报,1999,27(9)：130-132.
110.刘民,吴澄.解决并行多机提前／拖后调度问题的混合遗传算法方法[J].自动化学报,2006,26(2)：258-262.
111.刘民,吴澄,蒋新松.进化规划方法在并行多机调度问题中的应用[J].清华大学学报,(自然科学版)1998,38(8)：100-103.
112.刘民,吴澄.进化规划方法在最小化拖期任务数并行机调度问题中的应用[J].电子学报,1999,27(7)：132-134.
113. Anghinolfi D, Paolucci M. Parallel machine total tardiness scheduling with a new hybrid metaheuristic approach [J]. Computers & Operations Research,2007,34(11): 3471-3490.
114. Armentano V, Yamashita D. Tabu search for scheduling on identical parallel machines to minimize mean tardiness [J]. Journal of Intelligent Manufacturing,2000, 11(3):453-460.
115. Bilge O, Kirac F, Kurtulan M, et al. A tabu search algorithm for parallel machine total tardiness problem [J]. Computers & Operations Research,2004,31(2):397-414.
116. Ko H H, Beak J K, Kang Y H, et al. A scheduling scheme for restricted parallel machines with cycling process [J]. Journal of the Korean Institute of Industrial Engineers,2004,30(12):107-119.
117.梁旭,赵戈,王民生.改进的禁忌搜索算法求解多机并行模糊调度问题[J].大连交通大学学报,2009,30(4)：51-55.
118. Ying K-C, Cheng H-M. Dynamic parallel machine scheduling with sequence-dependent setup times using an iterated greedy heuristic [J]. Expert Systems with Applications,2010,37(4):2848-2852.
119. Koulamas C. Decomposition and hybrid simulated annealing heuristics for the parallel-machine total tardiness problem [J]. Naval Research Logist,1997,44(6): 105-125.
120. Kim D-W, Na D-G, Chen F F. Unrelated parallel machine scheduling with setup times and a total weighted tardiness objective [J]. Robotics and Computer-Integrated Manufacturing,2003,19(1-2):173-181.
121.高家全,方蕾.解非等同并行多机调度问题的并行遗传算法[J].计算机工程,2007,33(1)：198-200.
122.黄德才,郭海东.基于JIT的非等同并行多机调度问题的混合遗传算法[J].计算机集成制造系统,2004,10(3)：298-302.
123.Ghirardi M, Potts C N. Makespan minimization for scheduling unrelated parallel machines:A recovering beam search approach [J]. European Journal of Operational Research,2005,165(2):457-467.
124. Glass C A, Potts C N, Shade P. Unrelated parallel machine scheduling using local search [J]. Mathematical and Computer Modelling,1994,20(2):41-52.
125. Mokotoff E, Chretienne P. A cutting plane algorithm for the unrelated parallel machine sched uling problem [J]. European Journal of Operational Research,2002,141(3): 515-525.
126. Suresh V, Chaudhuri D. Bicriteria scheduling problem for unrelated parallel machines [J]. Computers & Industrial Engineering,1996,30(11):77-82.
127. Rasaratnam L, McDonell B, Smucker B. Scheduling unrelated parallel machines with sequence-dependent setups [J]. Computers & Operations Research,2007,34(11): 3420-3438.
128. Liaw C-F, Lin Y-K, Cheng C-Y, et al. Scheduling unrelated parallel machines to minimize total weighted tardiness [J]. Computers & Operations Research,2003,30(12): 1777-1789.
129. Li K, Yang S-L. Non-identical parallel-machine scheduling research with minimizing total weighted completion times:Models, relaxations and algorithms [J]. Applied Mathematical Modelling,2009,33(4):2145-2158.
130. Yang T. An evolutionary simulation-optimization approach in solving parallel-machine scheduling problems:A case study [J]. Computers & Industrial Engineering,2009,56(3):1126-1136.
131. Kim D W, Kim K H, Jang W, et al. Unrelated parellel machine scheduling with setup times using simulated annealing [J]. Robotics Computer Integrated Manufacturing, 2002,18(2):223-231.
132.刘文程,高家全,方志民.解优先级约束并行机调度问题的人工免疫算法[J].计算机工程与应用,2009,45(30)：208-211.
133.刘志雄,王少梅.基于粒子群算法的并行多机调度问题研究[J].计算机集成制造系统,2006,12(2)：183-188.
134. Yang J. The complexity of customer order scheduling problems on parallel machines [J]. Computers & Operations Research,2005,32(7):1921-1939.
135.曾齐红.基于遗传算法求解炼钢一连铸浇次排序问题[J].鞍山师范学院学报,2004,6(6)：70-73.
136.霍满臣,唐立新.面向流程工业的批在线调度问题[J].控制工程,2005,12(6)：511-514.
137. Gurel S, Selim M, Akturk. Scheduling parallel CNC machines with time/cost trade-off considerations [J]. Computers & Operations Research,2007,34(9):2774-2789.
138. Weng M X, Lu J, Ren H Y. Unrelated parallel machine scheduling with setup consideration and a total weighted completion time objective [J]. International Journal of Production Economics,2001,70(3):215-226.
139. Gao L, Wang C Y, Wang D W, et al. A production scheduling system for parallel machines in an electrical appliance plant [J]. Computers & Industrial Engineering,1998, 35(1-2):105-108.
140. Ziaee M, Sadjadi S J. Mixed binary integer programming formulations for the flow shop scheduling problems. A case study:ISD projects scheduling [J]. Applied Mathematics and Computation,2007,185(1):218-228.
141. Moslehi G, Mirzaee M, Vasei, M et al. Two-machine flow shop scheduling to minimize the sum of maximum earliness and tardiness [J]. International Journal of Production Economics,2009,122(2):763-773.
142. Zobolas G I, Tarantilis C D, Ioannou G. Minimizing makespan in permutation flow shop scheduling problems using a hybrid metaheuristic algorithm [J]. Computers & Operations Research,2009,36(4):1249-1267.
143. Xu J P, Zhou X Y. A class of multi-objective expected value decision-making model with birandom coefficients and its application to flow shop scheduling problem [J]. Information Sciences,2009,197(17):2997-3017.
144. Yagmahan B, Yenisey M M. A multi-objective ant colony system algorithm for flow shop scheduling problem [J]. Expert Systems with Applications,2010,37(2): 1361-1368.
145.王莉,朱晶.柔性Flow Shop调度问题的研究现状与发展趋势[J].鞍山师范学院学报,2002,4(1)：9-13.
146. Salvador M S. A solution of a special class of flow shop scheduling problems [C]. In Proceedings of the Symposium on the Theory of Scheduling and Its Applications, Berlin,1973.
147. Gputa J N D. Two-stage hybrid flowshop scheduling problem [J]. Journal of Operational Research Society,1988,39(4):359-364.
148. Brah S A, Hunsucker J L. Optimal scheduling in a flow shop with multiple processors [C]. The TIMS/ORSA Joint National Meeting, New Orleans.1987.
149. Brah S A, Hunsucker J L. Branch and bound algorithm for a flow shop with multiple processors [J]. European Journal of Operational Research,1991,51(1):88-99.
150. Bratley P, Florian M, Raobillard P. Scheduling with earlist start and due date constraints on multiple machines [J]. Naval Research Logistics,1990,22(1):165-173.
151. Rajendran C, Chaudhuri D. A multi-stage parallel processor flowshop problem with minimu flowtime [J]. European Journal of Operational Research,1992,57(6):111-122.
152. Rajendran C, Chaudhuri D. Scheduling in n-jobs, m-stage flowshops with parallel processors to minimize makespan [J]. International Journal of Production Economics, 1992,27(2):137-143.
153. Portmann M C, Vignier A, Dardilhac D, et al. Branch and bound crossed with GA to slove hybrid flowshops [J]. European Journal of Operational Research,1998,107(1): 389-400.
154. Riane F, Artiba A, Elmaghraby S E. A hybrid three-stage flowshop problem:Efficient heuristics to minimize makespan [J]. European Journal of Operational Research,1998, 109(6):321-329.
155. Moursli O, Pochet Y. A branch and bound algorithm for the hybrid flow shop [J]. International Journal of Production Economics,2000,64(3):113-125.
156. Neron E, Baptiste P, Gupta J N D. Solving hybrid flow shop problem using energetic reasoning and global operations [J]. Omega the Internationl Journal of Management Science,2001,29(3):501-511.
157. Allaoui H, Artiba A. Scheduling two stage hybrid flow shop with availability constraints [J]. Computers & Operations Research,2006,36(6):1399-1419.
158.轩华,唐立新.实时无等待HFS调度的一种拉格朗日松弛算法[J].控制与决策,2006,21(4)：376-380.
159.轩华,唐立新.带多处理器任务的动态混合流水车间调度问题[J].计算机集成制造系统,2007,13(11)：2254-2260.
160. Hunsucker J L, Shah R L. Performance of priority rules in a due date flow shop [J]. Omega the Internationl Journal of Management Science,1992,20(1):73-89.
161. Wittrock R J. Scheduling algorithms for flexible flow lines [J]. IBM Journal of Research and Development,1987,29(4):401-412.
162. Wittrock R J. An adaptable scheduling algorithm for flexible flow lines [J]. Operational Research,1988,33(4):445-453.
163. Soewnadi H, Elmaghraby S E. Sequencing three-stage flexible flowshops with identical machines to minimize makespan [J]. IIE Transactions,2001,31(1):985-993.
164. Guinet A G, Solomon M M. Scheduling hybrid flowshops to minimize maximum tardiness or maximum completion time [J]. International Journal of Production Research,1996,34(6):1643-1654.
165. Santos D L, Hunsucker J L, Deal D E. An evaluation of sequencing heuristics in flowshops with multiple processors [J]. Computer & Industrial Engineering,1996, 30(4):681-692.
166.崔建双,李铁克,张文新.混合流水车间调度模型及其遗传算法[J].北京科技大学学报,2005,27(5)：623-626.
167. Mohammad R A, Mohammad A B. Hybrid flow shop scheduling with parallel batching [J]. International Journal of Production Economics,2009,117(2):185-196.
168. Ceyda O, Ercan M F. A genetic algorithm for hybrid flowshop scheduling with multiprocessor tasks [J]. Journal of Scheduling,2005,8(1):323-351.
169. Tseng C-T, Liao C-J. A particle swarm optimization algorithm for hybrid flow-shop scheduling with multiprocessor tasks [J]. International Journal of Production Research, 2008,46(17):4655-4670.
170. Orhan E, Alper D. A new approach to solve hybrid flow shop scheduling problems by artificial immune system [J]. Future Generation Computer Systems,2004, 20(6):1083-1095.
171. Ceyda O, Yakov Z, Van H D, et al. Hybrid flow-shop scheduling problems with multiprocessor task systems [J]. European Journal of Operational Research,2004, 152(1):115-131.
172. Tsubone H. A production scheduling system for a hybrid flow shop:a case study [J]. Omega the Internationl Journal of Management Science,1993,21(2):205-214.
173. Hua X, Tang L X. Scheduling a hybrid flowshop with batch production at the last stage [J]. Computers & Operations Research,2007,34(11):2718-2733.
174.庞哈利,郑秉霖,徐心和.具有准时制工艺要求的混合FLOW SHOP调度问题——实例研究[J].信息与控制,1999,4：141-145.
175. Lin H-T, Liao C-J. A case study in a two-stage hybrid flow shop with setup time and dedicated machines [J]. International Journal of Production Economics,2003,86(2): 133-143.
176. Chen L, Bostel N, Dejax P, et al. A tabu search algorithm for the integrated scheduling problem of container handling systems in a martime terminal [J]. European Journal of Operational Research,2007,181(4):40-58.
177. Paul R L. A production scheduling problem in the glass container industry [J]. Operational Research,1979,27(2):290-302.
178. Tsubone H. Production scheduling system in the food manufacturing industry [C]. In 27th Conference Book of Zennohren Society, Japan,1975.
179.李明哲.轧钢轧辊生产热处理过程计划与调度问题研究[D].东北大学,2008.
180.覃一宁.冷轧薄板生产计划与调度系统的研究与应用[D].大连理工大学,2006.
181.宋道飞.钢厂生产作业计划与调度的自组织优化方法研究[D].重庆大学,2008.
182. Tang L X, Gong H. A hybrid two-stage transportation and batch scheduling problem [J]. Applied Mathematical Modelling,2008,32(12):2467-2479.
183. Yuan J J, Qi X L, Lu L F, et al. Single machine unbounded parallel-batch scheduling with forbidden intervals [J]. European Journal of Operational Research,2008,186(3): 1212-1217.
184. Lu L F, Cheng T C E, Yuan J J, et al. Bounded single-machine parallel-batch scheduling with release dates and rejection [J]. Computers & Operations Research, 2009,36(10):2748-2751.
185. Dobson G, Nambimadom R S. The batch loading and scheduling problem [J]. Operational Research,2001,49(1):52-65.
186. Mathirajan M, Sivakumar A I. Minimizing total weighted tardiness on heterogeneous batch processing machines with incompatible job families [J]. International Journal of Advanced Manufacturing Technology,2006,28(3):1038-1047.
187. Mathirajan M, Sivakumar Al, Chandru V. Scheduling algorithms and sensitivity analysis for heterogeneous batch processors with incompatible job families [J]. Journal of Industry Engeneering 2004,21(1):18-26.
188. Zee D J, van D, Van H-A, et al. On-line scheduling of multi-server batch operations [J]. HE Transactions,2001,33(1):569-586.
189. Balasubramanian H, Monch L, Fowler J, et al. Genetic algorithm based scheduling of parallel batch machines with incompatible job families to minimize total weighted tardiness [J]. International Journal of Production Research,2004,42(8):1621-1638.
190. Koh S-G, Koo P-H, Ha J-W, et al. Scheduling parallel batch processing machines with arbitrary job sizes and incompatible job families [J]. International Journal of Production Research,2004,42(19):4091-4107.
191. Lars M, Hari B, John W, et al. Heuristic scheduling of jobs on parallel batch machines with incompatible job families andunequal ready times [J]. Computers & Operations Research,2005,32(1):2731-2750.
192. Ali H K, Behrooz K, Masoud J. A hybrid genetic heuristic for scheduling parallel batch processing machines with arbitrary job sizes [J]. Computers & Operations Research, 2008,35(2):1084-1098.
193. Chang P-C, Chen S-H, Mani V. A note on due-date assignment and single machine scheduling with a learning/aging effect [J]. International Journal of Production Economics,2009,117(1):142-149.
194. Shabtay D, George S. Two due date assignment problems in scheduling a single machine [J]. Operations Research Letters,2006,34(6):683-691.
195. Shabtay D. Due date assignments and scheduling a single machine with a general earliness/tardiness cost function [J]. Computers & Operations Research,2008,35(5): 1539-1545.
196. Gur M, Assaf S. Scheduling a maintenance activity and due-window assignment on a single machine [J]. Computers & Operations Research,2009,36(9):2541-2545.
197. Gur M, Assaf S. Due-date assignment on uniform machines [J]. European Journal of Operational Research, Volume 193,2009,1(16):49-58.
198. Gabriella M, Ulrich M S, Gerhard J W. Parallel machine scheduling with nested job assignment restrictions [J]. Operations Research Letters,2010,38(1):47-50.
199. Richard L D, Stella Y H, Scott W. Heuristics for parallel-machine flexible-resource scheduling problems with unspecified job assignment [J]. Computers & Operations Research,1999,26(2):143-155.
200. Chen Z-L. Scheduling and common due date assignment with earliness-tardiness penalties and batch delivery costs [J]. European Journal of Operational Research,1996, 93(1):49-60.
201. Shabtay D. Scheduling and due date assignment to minimize earliness, tardiness, holding, due date assignment and batch delivery costs [J]. International Journal of Production Economics,2010,123(1):235-242.
202. Hoogeveen J A, Lenstra J K, Veltman B. Preemptive scheduling in a two-stage multiprocessor flow shop is NP-hard [J]. European Journal of Operational Research, 1996,89(1):172-175.
203. Grabowski J, Pempera J. Sequencing of jobs in some production system [J]. European Journal of Operational Research,2000,125(3):535-550.
204. Wang Z B, Xing W X, Bai F S. No-wait flexible flow shop scheduling with no-idle machines [J]. Operations Research Letters,2005,33(6):609-614.
205. Guirchoun S, Martineau P, Billaut J-C. Total completion time minimization in a computer system with a server and two parallel processors [J].Computers & Operations Research,2005,32(3):599-611.
206. Kennedy J, Eberhart R C. Particle Swarm Optimization [C]. IEEE International Conference on Neural Networks. Piscataway:IEEE Service Center,1995.1942-1948.
207.肖人彬,陶振武.群集智能研究进展[J].管理科学学报,2007,10(3)：82-96.
208. Kennedy J, Eberhart R C. A Discrete Binary Version of Particle Swarm Algorithm [C]. Proceedings of the 1997 Conference on System, Man, and Cybernetics. Piscataway: IEEE Service Center,1997:4104-4108.
209. Parsopoulos K E, Vrahatis M N. Recent approaches to global optimization problems through particle swarm optimization [J]. Natural Computing.2002,1(2-3):235-306.
2.高慧敏,曾建潮.钢铁生产调度智能优化与应用[M].北京：冶金工业出版社,2006,1-10.
3.刘均贤,韩静涛.冶金工业的发展及其对冶金轧辊的需求[J],大型铸锻件,2006,4：41-44.
4.俞誓达,陈菡.我国轧辊业现状及发展中应重视的问题[J],钢铁,2007,42(7)：1-6.
5. 贾建平.中国轧辊制造业技术现状与发展趋势(上)[J],中国钢铁业,2008,9：24-27.
6.2008-2010年中国轧辊行业研究与市场预测分析报告[R],中国行业研究报告网,2008,2-29.
7.吴素霞.计算机集成制造系统_CIMS_及其在我国的发展现状[J].科技与产业,2005,5(5)：62-64.
8.贾建平.中国轧辊制造业技术现状与发展趋势(下)[J],中国钢铁业,2008,10：27-31.
9. 薛灵虎.推进我国轧辊行业的技术进步[J],中国冶金,2002,61(6)：35-43.
10.徐继山.铸造合金半钢轧辊热处理工艺探讨[J],金属加工,2008,21：32-34.
11.金以慧,王诗亦,王桂增.过程控制的发展与展望[J].控制理论与应用,1997,14(2)：145-151.
12.徐俊刚,戴国忠,王宏安.生产调度理论和方法研究综述[J].计算机研究和发展,2004,41(2)：257-267.
13.蒋圣平,邹益仁,梁刚.钢铁企业CIMS下生产计划的研究[J],冶金自动化,2003,27(6)：1-6.
14.杨智茗,张洪伟,赵立.ERP生产规划系统的探索和实现[J],计算机工程与设计,2003,24(2)：46-49.
15.李锦飞,马汉武,陈纪南.生产管理与调度[M].北京：化工工业出版社,2005,77-80.
16.王丽莉,张凤荣.生产计划与控制[M].北京：机械工业出版社,2006,56-58.
17. Jorma K, Ovako O. The short term (1-15 months) planning and control of a steel plant [J]. Engineering and Process Economics,1979,4(2):235-243.
18. Rudi R. Developing a practical planning system for a steel business [J]. Long Range Planning, April 1986,19(2):90-100.
19. Tang L X. A review of planning and scheduling systems and methods for integrated steel production [J]. European Journal of Operational Research,2001,133(1):1-20.
20. Gershon M. Heuristic approaches for mine planning and production scheduling [J]. International Journal of Mining and Geological Engineering.1987,5(1):1-13.
21. Fabian T. Blast furnace production planning-a linear programming example [J]. Management Science,1967,14(2):1-27.
22.李建祥,唐立新,王梦光.钢铁企业的多品种多时段高炉生产计划问题研究[J].系统工程学报,2003,18(5)：438-446.
23.陈安福,罗运清.重钢中板生产计划优化及其对生产的影响[J].轧钢,2009,26(4)：52-54.
24.郑秉霖,胡琨元,常春光.一体化钢铁生产计划系统的研究现状与展望[J].控制工程,2003,(1)：6-10.
25. Liu Shixin, Tang Jiafu, Song Jianhai. Order-planning model and algorithm for manufacturing steel sheets [J]. International Journal of Production Economics,2006, 100(1):30-43.
26. Kumar A S, Srinivas, Tiwari M K. Modelling the slab stack shuffling problem in developing steel rolling schedules and its solution using improved Parallel Genetic Algorithms [J].International Journal of Production Economics,2004,91 (2):135-147.
27.唐立新CIMS下生产批量计划理论及其应用[M].北京：科学出版社,1998.
28. Ouelhadj D, Petrovic S, Cowling P I, et al.Inter-agent cooperation and communication for agent-based robust dynamic scheduling insteel production [J]. Advanced Engineering Informatics,2004,18 (3):161-172.
29. Denby B, SchofieldD, Bradford S. Neuralnetwork applications inmining engineering [R]. Nottingham:University of Nottingham,1991.
30. HafeezK, GriffithsM, Griffiths J, et al. Systems design of a two-echelon steel industry supply chain [J]. International Journal of Production Economics,1996,45(1-3): 121-130.
31. Bicheno J, Holweg M, Niessmann J. Constraint batch sizing in a lean environment [J]. International Journal of Production Economics,2001,73(2):41-49.
32. Taylor D H. Measurement and analysis of demand amplification across the supply chain [J]. International Journal of Logistics management,1999,10 (2):55-70.
33.李建祥,唐立新.钢铁供应链生产计划与调度研究综述[J].控制工程,2010,17(1)：123-126.
34. Goutam D, Robert F. A survey of mathematical programming applications in integrated steel plants [J]. IBM J RES DE-VELOPS,1997,58 (2):123-132.
35. Bellabdaoui A, Teghem J. A mixed-integer linear programming model for the continuous casting planning [J]. International Journal of Production Economics,2004, 124(3):1-11.
36. Peter C. A flexible decision support system for steel hot rolling mill scheduling [J]. Computers & Industrial Engineering,2003,45 (2):307-321.
37. Tang L X, Liu J Y, Rong A Y, et al. A multiple traveling salesman problem model for hot rolling scheduling in Shanghai Baoshan Iron & Steel Complex [J]. European Journal of Operational Research,2000,124 (2):267-282.
38. Bowers M R, Kaplan L A, Hooker T L. A two-phase model for Planning the production of aluminum ingot [J]. European Journal of Operational Research,1995,81(1): 105-114.
39.彭志刚,吴广宇,杨艳丽等.一机两流的连铸生产计划模型与算法[J].东北大学学报(自然科学版),2000,3：244-246.
40.史海波,马玉林,刘爱国.冶金冷轧薄板企业生产计划调度体系结构及方法研究[J].信息与控制,2004,2：31-35.
41. Tang L X, Liu J Y, Rong A Y, et al. A mathematical programming model for scheduling steel making-continuous casting production [J]. European Journal of Operational Research,2000, (2):423-435.
42. Narchal R M. A simulation model for corporate planning in a steel plant [J]. European Journal of Operational Research,1988,34(3):282-296.
43.李耀华,宁树实,王伟.基于准时制的轧钢厂生产计划模型及算法[J].控制工程,2004,2：321-324.
44.蒋圣平,邹益仁.钢铁企业年度生产计划的研究[J].控制与决策,2004,6：695-698.
45. Fox M S. Constraint-guided scheduling-A short history of research at CMU [J]. Computer in Industry,1990,14:79-88.
46. Rodammer F A, Whit K P. A recent survey of production scheduling [J]. IEEE Transactions on System Man and Cybernetic,1988,18(6):841-851.
47.王万良,吴启迪.生产调度智能算法及其应用[M].北京：科学出版社,2007,8-16.
48.柳毅.企业生产调度的智能优化方法[M].北京：人民邮电出版社,2008,5-10.
49. Huang X, Wang J B, Wang L Y, et al. Single machine scheduling with time-dependent deterioration and exponential learning effect [J]. Computers & Industrial Engineering, 2010,58(1):58-63.
50. Kuo W H, Yang D L. Single machine scheduling with past-sequence-dependent setup times and learning effects [J].Information Processing Letters,2007,102(1):22-26.
51. Jorge M S, Valente. Beam search heuristics for the single machine early/tardy scheduling problem with no machine idle time [J]. Computers & Industrial Engineering, 2008,55(3):663-675.
52.刘振刚,王道平,金峰.带组换装时间的单机调度问题[J].北京科技大学学报,2009,31(10)：1347-1350.
53. Adibi M A, Zandieh M, Amiri M. Multi-objective scheduling of dynamic job shop using variable neighborhood search [J]. Expert Systems with Applications,2010,37(1): 282-287.
54. Fawaz S A, Sotskov Y N, Allahverdi A, et al. Using mixed graph coloring to minimize total completion time in job shop scheduling [J]. Applied Mathematics and Computation,2006,182(2):1137-1148.
55. Guo Z X, Wong W K, Leung S Y, et al. Mathematical model and genetic optimization for the job shop scheduling problem in a mixed- and multi-product assembly environment:A case study based on the apparel industry [J]. Computers & Industrial Engineering,2006,50(3):202-219.
56. Zhang C Y, Li P G, Rao Y Q. A very fast TS/SA algorithm for the job shop scheduling problem [J]. Computers & Operations Research,2008,35(1):282-294.
57.唐立新,杨自厚,王梦光.基于准时制的炼钢-连铸生产调度问题研究[J].自动化学报,1998,24(1)：9-14.
58.方宇炜,韩曾晋.炼钢连铸过程的Petri网实时调度模型[J].清华大学学报,1999,39(1)：79-82.
59.孙福权,唐立新,郑秉霖.炼钢连铸生产调度专家系统[J].冶金自动化,1998,6：31-33.
60.李锦英,唐立新,王梦光.基于可视化虚拟现实技术的炼钢、连铸生产调度系统[J].冶金自动化,1999,4：14-17.
61.李霄峰,徐立云,邵惠鹤,任德祥.炼钢连铸系统的动态调度模型和启发式调度算法[J].上海交通大学学报,2001,35(11)：1658-1662.
62. Numao M, Morishita S. Cooperative scheduling and its application to steelmaking process [J]. IEEE Transaction on Industrial Electronics,1991,38(2):150-155.
63. Lally B, Biegler L. Henein H. A model for sequencing a continuous casting operation to minimize costs [J]. Iron and Steelmaker,1987,14(10):63-70.
64. Lee H S, Murthy S S, Haider S W, et al. Primary production scheduling at steelmaking industries [J]. IBM Journal of Research and Development,1996,40(2):231-252.
65. Meil D, Lee H S. Scheduling steel production on two twin-strand casters [C]. Proceedings of the International Manufacturing Productivity Symposium, NY,1993.
66. Takahashi T. Scheduling for steel making process using mathematical programming method [J]. Kobe Steel Engineering Reports,1990,40(3):29-32.
67. Neuwirth J. A production scheduling system at the stahlline GMBH [C]. International Conference on Computerized Production Control in Steel Plant, Korea,1993.
68. Tang L X, Yang Z H, Wang M G. Optimal model and algorithms for charge plan in steel-making and continuous casting production [J]. Journal of Northeastern University, 1996,17(4):440-445.
69. Tang L X, Yang Z H, Wang M G. Optimal model and algorithms for CAST plan in steel making and continuous casting production [J]. Journal of Northeastern University,1996, 17(5):554-558.
70. Tang L X, Yang Z H, Wang M G. Optimal model and algorithms for casting plan with unknown number of CAST in the steel making and continuous casting production [J]. Journal of Iron and Steel,1997,32(10):19-21.
71.徐心和,陈雄,郭念忠,谭金东.炼钢-连铸-热轧一体化管理[J].冶金自动化,1997,3：1-4.
72.唐立新,杨自厚,沈宏宇,胡国奋.炼钢-连铸-热轧集成批量计划因素分析[J].钢铁,2000,35(5)：74-76.
73.孙福权,郑秉霖,唐立新,崔建江,冯少丽.炼钢-连铸-热轧一体化集成调度管理[J].钢铁,1998,33(12)：71-75.
74.孙福权,郑秉霖,崔建江,汪定伟,刘新胜.炼钢-热轧一体化管理的生产计划编制问题研究[J].自动化学报,2000,26(3)：409-413.
75.张彩霞,石亦平,贺城江,韩静涛,贺毓辛.冶铸轧一体化生产调度方法的探讨[J].钢铁,2000,35(2)：74-77.
76.朱宝琳,于海斌.炼钢-连铸-热轧生产调度模型及算法研究[J].计算机集成制造系统,2003,9(1)：33-36.
77.于银俊,易先堂,王尚勤.运用微机管理优化连铸连轧生产调度计划方法的探讨[J].冶金信息导刊,2001,5：24-26.
78.彭其春,包燕平,田乃媛,王德城.一体化生产管理系统炼钢计划子系统设计[J].北京科技大学学报,2002,24(1)：25-28.
79. Peter C, Rezig W. Integrated of continuous caster and hot strip mill planning for steel production [J]. Journal of Scheduling,2000,36(3):185-208.
80. Tamura R, Nagai N, Nakagawa Y, et al. Functionally partitioned scheduling system equipped with two-stage scheduling algorithm in steel sheet manufacturing [J]. Instruments and Automatic Control,1995,8(10):592-601.
81.王芸凤.智能生产调度方法的研究与应用[D].合肥：合肥工业大学,2005.
82.玄光男,程润伟.遗传算法与工程设计[M].汪定伟,唐加福,黄敏译.北京：科学出版社,2000,171-173.
83. McNaughton R. Scheduling with deadlines and loss functions [J]. Management Science, 1959,6(1):1-12.
84. Garey M, Johnson D. Strong NP-completeness results:motivation, examples and implications [J]. Journal of ACM,1978,25(9):499-508.
85. Bruno L, Coffman J, Sethi R. Scheduling independent tasks to reduce mean finishing time [J]. Communications on ACM,1974,17(6):382-387.
86. Li C, Cheng T. The parallel machine min-max weighted absolute lateness scheduling problem [J]. Naval Research Logistics,1993,41(3):33-46.
87. Chu C B, Yalaoui F. Parallel machine scheduling to minimize total tardiness [J]. International Journal of Production Economics,2002,76(3):265-279.
88. Kim Y-D, Shim S-O. Scheduling on parallel identical machines to minimize total tardiness [J]. European Journal of Operational Research,2007,177(1):135-146.
89. Kim Y-D, Shim S-O. A branch and bound algorithm for an identical parallel machine scheduling problem with a job splitting property [J]. Computers & Operations Research, 2008,35(3):863-875
90. Dogramaci A, Surkis J. Evaluation of a heuristics for scheduling independent jobs on parallel identical processors [J]. Management Science,1979,25(4):1208-1216.
91. Ho J C, Chang Y-L. Heuristics for minimizing mean tardiness for m parallel machines [J]. Naval Research Logistics,1991,38(5):367-381.
92. Alidaee B, Rosa D. Scheduling parallel machines to minimize total weighted and un-weighted tardiness [J]. Computers & Operations Research,1997,24(8):775-788.
93. Biskup D, Herrmann J, Gupta J N D. Scheduling identical parallel machines to minimize total tardiness [J]. International Journal of Production Economics,2008, 115(1):134-142.
94. Xu D H, Cheng Z, Yin Y, Li H X. Makespan minimization for two parallel machines scheduling with a periodic availability constraint [J]. Computers & Operations Research,2009,36(6):1809-1812.
95. Vinicius A, Armentano, Moacir F. Minimizing total tardiness in parallel machine scheduling with setup times:An adaptive memory-based GRASP approach [J]. European Journal of Operational Research,2007,183(1):100-114.
96. Xu D H, Sun K B, Li H X. Parallel machine scheduling with almost periodic maintenance and non-preemptive jobs to minimize makespan [J]. Computers & Operations Research,2008,35(4):1344-1349.
97. Kim E-S, Sung C-S, Lee I-S. Scheduling of parallel machines to minimize total completion time subject to s-precedence constraints [J]. Computers & Operations Research,2009,36(3):698-710.
98. Wang X L, Cheng T C E. Heuristics for parallel-machine scheduling with job class setups and delivery to multiple customers [J]. International Journal of Production Economics,2009,119(1):199-206.
99.时维国,宋存利,黄明.基于启发式算法的并行多机调度问题研究[J].大连铁道学院学报,2003,24(4)：55-58.
100. Mateus R P, Mateus G R, Ravetti M G. A non-delayed relax-and-cut algorithm for scheduling problems with parallel machines, due dates and sequence-dependent setup times [J]. Computers & Operations Research,2010,37(5):938-949.
101.宁凝,钱省三,孟志雷.带有工艺约束的并行多机调度策略[J].工业工程,2008,11(2)：62-65.
102. Cheng R, Gen M, Tozawa T. Minmax earliness/tardiness scheduling in identical parallel machine system using genetic algorithms [J]. Computers & Industrial Engineering,1995,29(1-4):513-517.
103.何敬东,黄向,严太山.并行机调度遗传算法研究[J].大众科技,2008,6：54-56.
104.朱长武,戴上平,刘智.并行遗传算法在并行多机调度中的应用[J].微计算机信息,2007,23(2-3)：200-201.
105.吴昊,程锦松.用并行遗传算法解决带约束并行多机调度问题[J].微机发展,2001,1：19-22.
106.何桂霞,高家全,王雨顺.特殊工艺约束并行多机双目标调度问题的研究[J].计算机工程与应用,2008,44(32)：197-200.
107.周辉仁.递阶遗传算法理论及其应用研究[D].天津大学,2008.
108.周辉仁,郑丕鄂,王海龙.基于递阶遗传算法的最小加权完土时间并行机调度[J].系统仿真学报,2008,20(13)：3510-3513.
109.刘民,吴澄,戴元顺.最小化拖期任务数并行机调度问题的一种基于知识的遗传算法[J].电子学报,1999,27(9)：130-132.
110.刘民,吴澄.解决并行多机提前／拖后调度问题的混合遗传算法方法[J].自动化学报,2006,26(2)：258-262.
111.刘民,吴澄,蒋新松.进化规划方法在并行多机调度问题中的应用[J].清华大学学报,(自然科学版)1998,38(8)：100-103.
112.刘民,吴澄.进化规划方法在最小化拖期任务数并行机调度问题中的应用[J].电子学报,1999,27(7)：132-134.
113. Anghinolfi D, Paolucci M. Parallel machine total tardiness scheduling with a new hybrid metaheuristic approach [J]. Computers & Operations Research,2007,34(11): 3471-3490.
114. Armentano V, Yamashita D. Tabu search for scheduling on identical parallel machines to minimize mean tardiness [J]. Journal of Intelligent Manufacturing,2000, 11(3):453-460.
115. Bilge O, Kirac F, Kurtulan M, et al. A tabu search algorithm for parallel machine total tardiness problem [J]. Computers & Operations Research,2004,31(2):397-414.
116. Ko H H, Beak J K, Kang Y H, et al. A scheduling scheme for restricted parallel machines with cycling process [J]. Journal of the Korean Institute of Industrial Engineers,2004,30(12):107-119.
117.梁旭,赵戈,王民生.改进的禁忌搜索算法求解多机并行模糊调度问题[J].大连交通大学学报,2009,30(4)：51-55.
118. Ying K-C, Cheng H-M. Dynamic parallel machine scheduling with sequence-dependent setup times using an iterated greedy heuristic [J]. Expert Systems with Applications,2010,37(4):2848-2852.
119. Koulamas C. Decomposition and hybrid simulated annealing heuristics for the parallel-machine total tardiness problem [J]. Naval Research Logist,1997,44(6): 105-125.
120. Kim D-W, Na D-G, Chen F F. Unrelated parallel machine scheduling with setup times and a total weighted tardiness objective [J]. Robotics and Computer-Integrated Manufacturing,2003,19(1-2):173-181.
121.高家全,方蕾.解非等同并行多机调度问题的并行遗传算法[J].计算机工程,2007,33(1)：198-200.
122.黄德才,郭海东.基于JIT的非等同并行多机调度问题的混合遗传算法[J].计算机集成制造系统,2004,10(3)：298-302.
123.Ghirardi M, Potts C N. Makespan minimization for scheduling unrelated parallel machines:A recovering beam search approach [J]. European Journal of Operational Research,2005,165(2):457-467.
124. Glass C A, Potts C N, Shade P. Unrelated parallel machine scheduling using local search [J]. Mathematical and Computer Modelling,1994,20(2):41-52.
125. Mokotoff E, Chretienne P. A cutting plane algorithm for the unrelated parallel machine sched uling problem [J]. European Journal of Operational Research,2002,141(3): 515-525.
126. Suresh V, Chaudhuri D. Bicriteria scheduling problem for unrelated parallel machines [J]. Computers & Industrial Engineering,1996,30(11):77-82.
127. Rasaratnam L, McDonell B, Smucker B. Scheduling unrelated parallel machines with sequence-dependent setups [J]. Computers & Operations Research,2007,34(11): 3420-3438.
128. Liaw C-F, Lin Y-K, Cheng C-Y, et al. Scheduling unrelated parallel machines to minimize total weighted tardiness [J]. Computers & Operations Research,2003,30(12): 1777-1789.
129. Li K, Yang S-L. Non-identical parallel-machine scheduling research with minimizing total weighted completion times:Models, relaxations and algorithms [J]. Applied Mathematical Modelling,2009,33(4):2145-2158.
130. Yang T. An evolutionary simulation-optimization approach in solving parallel-machine scheduling problems:A case study [J]. Computers & Industrial Engineering,2009,56(3):1126-1136.
131. Kim D W, Kim K H, Jang W, et al. Unrelated parellel machine scheduling with setup times using simulated annealing [J]. Robotics Computer Integrated Manufacturing, 2002,18(2):223-231.
132.刘文程,高家全,方志民.解优先级约束并行机调度问题的人工免疫算法[J].计算机工程与应用,2009,45(30)：208-211.
133.刘志雄,王少梅.基于粒子群算法的并行多机调度问题研究[J].计算机集成制造系统,2006,12(2)：183-188.
134. Yang J. The complexity of customer order scheduling problems on parallel machines [J]. Computers & Operations Research,2005,32(7):1921-1939.
135.曾齐红.基于遗传算法求解炼钢一连铸浇次排序问题[J].鞍山师范学院学报,2004,6(6)：70-73.
136.霍满臣,唐立新.面向流程工业的批在线调度问题[J].控制工程,2005,12(6)：511-514.
137. Gurel S, Selim M, Akturk. Scheduling parallel CNC machines with time/cost trade-off considerations [J]. Computers & Operations Research,2007,34(9):2774-2789.
138. Weng M X, Lu J, Ren H Y. Unrelated parallel machine scheduling with setup consideration and a total weighted completion time objective [J]. International Journal of Production Economics,2001,70(3):215-226.
139. Gao L, Wang C Y, Wang D W, et al. A production scheduling system for parallel machines in an electrical appliance plant [J]. Computers & Industrial Engineering,1998, 35(1-2):105-108.
140. Ziaee M, Sadjadi S J. Mixed binary integer programming formulations for the flow shop scheduling problems. A case study:ISD projects scheduling [J]. Applied Mathematics and Computation,2007,185(1):218-228.
141. Moslehi G, Mirzaee M, Vasei, M et al. Two-machine flow shop scheduling to minimize the sum of maximum earliness and tardiness [J]. International Journal of Production Economics,2009,122(2):763-773.
142. Zobolas G I, Tarantilis C D, Ioannou G. Minimizing makespan in permutation flow shop scheduling problems using a hybrid metaheuristic algorithm [J]. Computers & Operations Research,2009,36(4):1249-1267.
143. Xu J P, Zhou X Y. A class of multi-objective expected value decision-making model with birandom coefficients and its application to flow shop scheduling problem [J]. Information Sciences,2009,197(17):2997-3017.
144. Yagmahan B, Yenisey M M. A multi-objective ant colony system algorithm for flow shop scheduling problem [J]. Expert Systems with Applications,2010,37(2): 1361-1368.
145.王莉,朱晶.柔性Flow Shop调度问题的研究现状与发展趋势[J].鞍山师范学院学报,2002,4(1)：9-13.
146. Salvador M S. A solution of a special class of flow shop scheduling problems [C]. In Proceedings of the Symposium on the Theory of Scheduling and Its Applications, Berlin,1973.
147. Gputa J N D. Two-stage hybrid flowshop scheduling problem [J]. Journal of Operational Research Society,1988,39(4):359-364.
148. Brah S A, Hunsucker J L. Optimal scheduling in a flow shop with multiple processors [C]. The TIMS/ORSA Joint National Meeting, New Orleans.1987.
149. Brah S A, Hunsucker J L. Branch and bound algorithm for a flow shop with multiple processors [J]. European Journal of Operational Research,1991,51(1):88-99.
150. Bratley P, Florian M, Raobillard P. Scheduling with earlist start and due date constraints on multiple machines [J]. Naval Research Logistics,1990,22(1):165-173.
151. Rajendran C, Chaudhuri D. A multi-stage parallel processor flowshop problem with minimu flowtime [J]. European Journal of Operational Research,1992,57(6):111-122.
152. Rajendran C, Chaudhuri D. Scheduling in n-jobs, m-stage flowshops with parallel processors to minimize makespan [J]. International Journal of Production Economics, 1992,27(2):137-143.
153. Portmann M C, Vignier A, Dardilhac D, et al. Branch and bound crossed with GA to slove hybrid flowshops [J]. European Journal of Operational Research,1998,107(1): 389-400.
154. Riane F, Artiba A, Elmaghraby S E. A hybrid three-stage flowshop problem:Efficient heuristics to minimize makespan [J]. European Journal of Operational Research,1998, 109(6):321-329.
155. Moursli O, Pochet Y. A branch and bound algorithm for the hybrid flow shop [J]. International Journal of Production Economics,2000,64(3):113-125.
156. Neron E, Baptiste P, Gupta J N D. Solving hybrid flow shop problem using energetic reasoning and global operations [J]. Omega the Internationl Journal of Management Science,2001,29(3):501-511.
157. Allaoui H, Artiba A. Scheduling two stage hybrid flow shop with availability constraints [J]. Computers & Operations Research,2006,36(6):1399-1419.
158.轩华,唐立新.实时无等待HFS调度的一种拉格朗日松弛算法[J].控制与决策,2006,21(4)：376-380.
159.轩华,唐立新.带多处理器任务的动态混合流水车间调度问题[J].计算机集成制造系统,2007,13(11)：2254-2260.
160. Hunsucker J L, Shah R L. Performance of priority rules in a due date flow shop [J]. Omega the Internationl Journal of Management Science,1992,20(1):73-89.
161. Wittrock R J. Scheduling algorithms for flexible flow lines [J]. IBM Journal of Research and Development,1987,29(4):401-412.
162. Wittrock R J. An adaptable scheduling algorithm for flexible flow lines [J]. Operational Research,1988,33(4):445-453.
163. Soewnadi H, Elmaghraby S E. Sequencing three-stage flexible flowshops with identical machines to minimize makespan [J]. IIE Transactions,2001,31(1):985-993.
164. Guinet A G, Solomon M M. Scheduling hybrid flowshops to minimize maximum tardiness or maximum completion time [J]. International Journal of Production Research,1996,34(6):1643-1654.
165. Santos D L, Hunsucker J L, Deal D E. An evaluation of sequencing heuristics in flowshops with multiple processors [J]. Computer & Industrial Engineering,1996, 30(4):681-692.
166.崔建双,李铁克,张文新.混合流水车间调度模型及其遗传算法[J].北京科技大学学报,2005,27(5)：623-626.
167. Mohammad R A, Mohammad A B. Hybrid flow shop scheduling with parallel batching [J]. International Journal of Production Economics,2009,117(2):185-196.
168. Ceyda O, Ercan M F. A genetic algorithm for hybrid flowshop scheduling with multiprocessor tasks [J]. Journal of Scheduling,2005,8(1):323-351.
169. Tseng C-T, Liao C-J. A particle swarm optimization algorithm for hybrid flow-shop scheduling with multiprocessor tasks [J]. International Journal of Production Research, 2008,46(17):4655-4670.
170. Orhan E, Alper D. A new approach to solve hybrid flow shop scheduling problems by artificial immune system [J]. Future Generation Computer Systems,2004, 20(6):1083-1095.
171. Ceyda O, Yakov Z, Van H D, et al. Hybrid flow-shop scheduling problems with multiprocessor task systems [J]. European Journal of Operational Research,2004, 152(1):115-131.
172. Tsubone H. A production scheduling system for a hybrid flow shop:a case study [J]. Omega the Internationl Journal of Management Science,1993,21(2):205-214.
173. Hua X, Tang L X. Scheduling a hybrid flowshop with batch production at the last stage [J]. Computers & Operations Research,2007,34(11):2718-2733.
174.庞哈利,郑秉霖,徐心和.具有准时制工艺要求的混合FLOW SHOP调度问题——实例研究[J].信息与控制,1999,4：141-145.
175. Lin H-T, Liao C-J. A case study in a two-stage hybrid flow shop with setup time and dedicated machines [J]. International Journal of Production Economics,2003,86(2): 133-143.
176. Chen L, Bostel N, Dejax P, et al. A tabu search algorithm for the integrated scheduling problem of container handling systems in a martime terminal [J]. European Journal of Operational Research,2007,181(4):40-58.
177. Paul R L. A production scheduling problem in the glass container industry [J]. Operational Research,1979,27(2):290-302.
178. Tsubone H. Production scheduling system in the food manufacturing industry [C]. In 27th Conference Book of Zennohren Society, Japan,1975.
179.李明哲.轧钢轧辊生产热处理过程计划与调度问题研究[D].东北大学,2008.
180.覃一宁.冷轧薄板生产计划与调度系统的研究与应用[D].大连理工大学,2006.
181.宋道飞.钢厂生产作业计划与调度的自组织优化方法研究[D].重庆大学,2008.
182. Tang L X, Gong H. A hybrid two-stage transportation and batch scheduling problem [J]. Applied Mathematical Modelling,2008,32(12):2467-2479.
183. Yuan J J, Qi X L, Lu L F, et al. Single machine unbounded parallel-batch scheduling with forbidden intervals [J]. European Journal of Operational Research,2008,186(3): 1212-1217.
184. Lu L F, Cheng T C E, Yuan J J, et al. Bounded single-machine parallel-batch scheduling with release dates and rejection [J]. Computers & Operations Research, 2009,36(10):2748-2751.
185. Dobson G, Nambimadom R S. The batch loading and scheduling problem [J]. Operational Research,2001,49(1):52-65.
186. Mathirajan M, Sivakumar A I. Minimizing total weighted tardiness on heterogeneous batch processing machines with incompatible job families [J]. International Journal of Advanced Manufacturing Technology,2006,28(3):1038-1047.
187. Mathirajan M, Sivakumar Al, Chandru V. Scheduling algorithms and sensitivity analysis for heterogeneous batch processors with incompatible job families [J]. Journal of Industry Engeneering 2004,21(1):18-26.
188. Zee D J, van D, Van H-A, et al. On-line scheduling of multi-server batch operations [J]. HE Transactions,2001,33(1):569-586.
189. Balasubramanian H, Monch L, Fowler J, et al. Genetic algorithm based scheduling of parallel batch machines with incompatible job families to minimize total weighted tardiness [J]. International Journal of Production Research,2004,42(8):1621-1638.
190. Koh S-G, Koo P-H, Ha J-W, et al. Scheduling parallel batch processing machines with arbitrary job sizes and incompatible job families [J]. International Journal of Production Research,2004,42(19):4091-4107.
191. Lars M, Hari B, John W, et al. Heuristic scheduling of jobs on parallel batch machines with incompatible job families andunequal ready times [J]. Computers & Operations Research,2005,32(1):2731-2750.
192. Ali H K, Behrooz K, Masoud J. A hybrid genetic heuristic for scheduling parallel batch processing machines with arbitrary job sizes [J]. Computers & Operations Research, 2008,35(2):1084-1098.
193. Chang P-C, Chen S-H, Mani V. A note on due-date assignment and single machine scheduling with a learning/aging effect [J]. International Journal of Production Economics,2009,117(1):142-149.
194. Shabtay D, George S. Two due date assignment problems in scheduling a single machine [J]. Operations Research Letters,2006,34(6):683-691.
195. Shabtay D. Due date assignments and scheduling a single machine with a general earliness/tardiness cost function [J]. Computers & Operations Research,2008,35(5): 1539-1545.
196. Gur M, Assaf S. Scheduling a maintenance activity and due-window assignment on a single machine [J]. Computers & Operations Research,2009,36(9):2541-2545.
197. Gur M, Assaf S. Due-date assignment on uniform machines [J]. European Journal of Operational Research, Volume 193,2009,1(16):49-58.
198. Gabriella M, Ulrich M S, Gerhard J W. Parallel machine scheduling with nested job assignment restrictions [J]. Operations Research Letters,2010,38(1):47-50.
199. Richard L D, Stella Y H, Scott W. Heuristics for parallel-machine flexible-resource scheduling problems with unspecified job assignment [J]. Computers & Operations Research,1999,26(2):143-155.
200. Chen Z-L. Scheduling and common due date assignment with earliness-tardiness penalties and batch delivery costs [J]. European Journal of Operational Research,1996, 93(1):49-60.
201. Shabtay D. Scheduling and due date assignment to minimize earliness, tardiness, holding, due date assignment and batch delivery costs [J]. International Journal of Production Economics,2010,123(1):235-242.
202. Hoogeveen J A, Lenstra J K, Veltman B. Preemptive scheduling in a two-stage multiprocessor flow shop is NP-hard [J]. European Journal of Operational Research, 1996,89(1):172-175.
203. Grabowski J, Pempera J. Sequencing of jobs in some production system [J]. European Journal of Operational Research,2000,125(3):535-550.
204. Wang Z B, Xing W X, Bai F S. No-wait flexible flow shop scheduling with no-idle machines [J]. Operations Research Letters,2005,33(6):609-614.
205. Guirchoun S, Martineau P, Billaut J-C. Total completion time minimization in a computer system with a server and two parallel processors [J].Computers & Operations Research,2005,32(3):599-611.
206. Kennedy J, Eberhart R C. Particle Swarm Optimization [C]. IEEE International Conference on Neural Networks. Piscataway:IEEE Service Center,1995.1942-1948.
207.肖人彬,陶振武.群集智能研究进展[J].管理科学学报,2007,10(3)：82-96.
208. Kennedy J, Eberhart R C. A Discrete Binary Version of Particle Swarm Algorithm [C]. Proceedings of the 1997 Conference on System, Man, and Cybernetics. Piscataway: IEEE Service Center,1997:4104-4108.
209. Parsopoulos K E, Vrahatis M N. Recent approaches to global optimization problems through particle swarm optimization [J]. Natural Computing.2002,1(2-3):235-306.