给水管网优化设计及其CAD的研究
|
摘要
随着城市现代化建设的加快，配水管网建设在市政工程中占有了越来越重要的地位。由于给水管网优化技术的运用能够产生巨大的经济效益和社会效益，不仅可以节省大量的资金，而且还能改善整个管网的水力条件，因此具有很好的工程前景；然而目前管网优化技术缺乏工程实用功能，而且计算机作为一种强大的现代工具，并没能得到充分的应用。本文根据以往的文献资料及相关工程经验，针对给水管网优化设计这一课题做了深入的研究，提出利用分层分解协调算法将管网优化设计问题分解成流量优化、管径优化及管径取整三个子课题的思想，并分别采用广义简约梯度法、遗传算法与广义简约梯度法相结合的混合遗传算法及简单遗传算法来求解三个课题。本文对遗传算法作了很多的改进，采用了自然数编码技术、扩大采样空间技术、惩罚策略、算术交叉和动态变异技术，并将遗传算法与GRG法有机地结合起来，改善了遗传算法的性能，充分地提高了搜索的效率和精度。本文还开发了以优化技术为核心的给水管网CAD，实现了在CAD中自动搜索并提取管网的拓扑信息及节点流量的自动预分配，建立了管网信息的Access数据库，从而能更为方便地进行管网优化设计。此外，本文以Visual C++作为管网数据库开发平台，实现了对数据库数据的提取，优化计算以及数据反馈。最后，本文结合工程实例验证了算法以及管网CAD的实用性。
With the development of the city modernization, municipal water supply system becomes more and more important in the municipal engineering. Because optimal technology of the water supply networks can not only save a great deal of funds but also improve the hydraulic condition of the whole network, it has better practical value. Although using optimal technology can make great economic effectiveness and social effectiveness, it lacks of practical function. Moreover, the computer that is a modern tool has not been widely used in the field. Using the literature materials and experience before, this paper makes a thorough study on optimal design of water supply networks. An algorithm of decomposing and coordination of system engineering which divides the optimization of the whole networks into three parts, i.e. optimization of water resource flow, and pipe-diameter and standardization of pipe-diameter is proposed. The three parts can be resolved by generalized contracted grads method, hybrid genetic algorithm which is the combination of genetic algorithm and GRG method separately. This paper also makes many reforms on genetic algorithm, which include using the technology of the real number code, broadening the selecting space, punishment tactics, arithmetical crossover, dynamic mutation and combining genetic algorithm with GRG method, so it brings faster searching velocity and better accuracy. Next through program Graphic databases and databases of water supply pipeline network are created by means of auto-searching the topological information of pipeline network, auto-numbering the pipelines and the joints, and measuring the length of pipelines and the flow distribution of initial pipelines from CAD. What's more, Through Visual C++, getting data from databases, optimal design and returning data back to databases are achieved. At last, the water supply networks CAD system and optimal method is tested and verified in an example.
With the development of the city modernization, municipal water supply system becomes more and more important in the municipal engineering. Because optimal technology of the water supply networks can not only save a great deal of funds but also improve the hydraulic condition of the whole network, it has better practical value. Although using optimal technology can make great economic effectiveness and social effectiveness, it lacks of practical function. Moreover, the computer that is a modern tool has not been widely used in the field. Using the literature materials and experience before, this paper makes a thorough study on optimal design of water supply networks. An algorithm of decomposing and coordination of system engineering which divides the optimization of the whole networks into three parts, i.e. optimization of water resource flow, and pipe-diameter and standardization of pipe-diameter is proposed. The three parts can be resolved by generalized contracted grads method, hybrid genetic algorithm which is the combination of genetic algorithm and GRG method separately. This paper also makes many reforms on genetic algorithm, which include using the technology of the real number code, broadening the selecting space, punishment tactics, arithmetical crossover, dynamic mutation and combining genetic algorithm with GRG method, so it brings faster searching velocity and better accuracy. Next through program Graphic databases and databases of water supply pipeline network are created by means of auto-searching the topological information of pipeline network, auto-numbering the pipelines and the joints, and measuring the length of pipelines and the flow distribution of initial pipelines from CAD. What's more, Through Visual C++, getting data from databases, optimal design and returning data back to databases are achieved. At last, the water supply networks CAD system and optimal method is tested and verified in an example.
引文
[1] 霍倩，李书全，韩会玲．城市配水管网优化设计．海河水利，2001，(2)：16～18
[2] Amy J.Purves, A Lee Cesario. Computer applications in the water industry. J.AWWA, 1993, (4): 129～130
[3] 俞国平．给水管网优化设计的新方法——广义简约梯度法．给水排水，1988，14(5)：15～21
[4] 解可新，韩立兴，林友联．最优化方法．天津：天津大学出版社，2002
[5] 周明，孙树栋．遗传算法原理及应用．北京：国防工业出版社，1999
[6] 许仕荣，邱振华．给水管网的计算理论与电算应用．长沙：湖南大学出版社，1997
[7] 王峪飞，俞国平，彭丽娜．关于给水管道技术经济计算模型的讨论．给水排水，2001，27(3)：46～47
[8] 汪国焘．城市供水行业2000年技术进步发展规划．北京：中国建筑工业出版社，1993
[9] 周建华，赵洪宾．城市给水管网系统所面临的问题及对策．中国给水排水，2002，18(11)：30～32
[10] Morgan D.R, Goulter I.C.Optional Urban Water Distribution Design. Water Resource Research, 1985, 20(6): 642～652
[11] Kessler A, Shamir U. Decomposition Technique for Optimal Design of Water Supply Networks. Engineering Optimization, 1991, 17(1): 1～19
[12] 仲伟俊，徐南荣，沈厚才．管网系统改造优化设计问题的模型及分层分解算法．系统工程学报，1994，9(2)：11～19
[13] Mitler L G. Branch, Bound Mcthods. General Formulation and Properties. Operations Research, 1970, 18(1): 24～34
[14] 仲伟俊，徐南荣，沈厚才．供水网络系统改造的智能化计算机辅助设计．信息与控制，1995，24(6)：373～376
[15] 袁一星，陈兵，李玉华等．多水源供水管网流量分布的研究．给水排水，1998，24(5)：15～19
[16] 沈致和．“最短树”的多水源给水管网流量分配．工业用水与废水，1996，(4)：
1～4
[17] 袁亚湘，孙文瑜．最优化理论与方法．北京：科学出版社，1999
[18] 韩炜，廖振鹏．关于遗传算法收敛性的注记．地震工程与工程振动，1999，19(4)：13～16
[19] Goldberg D. Genetic Algorithms in Reareh, Optimization and Machine Learning. Addison Wesley: Reading(MA), 1989
[20] 玄光男(日)，程润伟．遗传算法与工程设计．北京：科学出版社，2000
[21] Michalewicz Z. Genetic Algorithm+Data Structure=Evolution Programs(2nd ed). New York: Spring-Verlag, 1994
[22] Holland J. Adaptation in Natural and Artificial System. Ann Arobor: Univerity of Michigan Press, 1975
[23] Goldberg D E. Optimal Initial Population Size for Binary-Coded Genetic Algorithms(M). TCGA Report, University of Alabama, 1995
[24] 李大卫．可重复自然数编码遗传算法的最优群体规模．鞍山钢铁学院学报，2000，23(6)：419～423
[25] Davis L. Adapting Operator Probabilities in Genetic Algorithms. In: Proc. of. 3rd Int. Conf. on Genetic Algorithms, Morgan Kaufmann, 1989:61～69
[26] Whitley D. et al. Genitor Ⅱ: A Distributed Genetic Algorithm. J. Expt. Ther. Intell, 1990, (2): 189～214
[27] 王煦法．遗传算法及其应用．小型微型计算机系统，1995，16(2)：59～64
[28] 王文远，Davison Mwale．提高基因算法求管网经济管径计算效率的尝试．给水排水，2000，26(2)：32～34
[29] Michalewicz Z. et al. Genetic Algorithms and Optimal Control Problem. In: Proc. of 29th IEEE Conf. on Decision and Control, 1990:1664～1666
[30] Jemikow C Z, Michalewicz Z. An Experimental Comparison of Binary and Floating Point Representation in Genetic Algorithm. In: Proc. of 4th Int. Conf. on Genetic Algorithms. Morgan Kaufmann, 1991:31～36
[31] 张美恋．基于遗传算法和单纯形法的混合优化算法．集美大学学报，2001，6(2)：106～110
[32] Fogel D. An Introduction to Simulated Evolutionary Optimization. IEEE Transactions on Neural Networks, 1994, 5: 3～14
[33] Schwefel H. Evolution and Optimum Seeking. New York: John Wiley &
Sons, 1994
[34] Grefenstette J. Proceedings of the Second International Conference on Genetic Algorithms. Hillsdale: Lawrence Erlbaum Associates(NJ), 1995
[35] Kim J H, H Myung. A two-phase evolutionary programming for general constrained optimization problem. In: Proc. of the Fifth Conference on Evolutionary Programming. San Diego: 1996
[36] Eshelman L J. Proceedings of Sixth International Conference on Genetic Algorithms. San Francisco: Morgan Kaufmann Publishers, 1995
[37] Myung H, JH Kim. Hybrid evolutionary programming for heavily constraimed problems. Bio-Systems, 1996, 38: 29～43
[38] Fogel D. Proceedings of the First IEEE Conference on Evolutionary Computation. Orlando: IEEE Press, 1994
[39] McDonnell J, R Reynolds, D Fogel. Evolutionary Programming Ⅳ. Cambridge: MIT Press, 1995
[40] Michalewicz Z, D Dasgupta, R G Le Riche et al. Evolutionary algorithms for Industrial Engineering problems. International Journal of Computers and Industrial Engineering, 1996, 30(4)
[41] Davis L. Handbook of Genetic Alogrithms. New York: Van Nostrand Reinhold, 1991
[42] Spears W, K De Jong. On the virtues of parameterized uniform cross-over. In: Proceedings of the Fourth International Conference on Genetic Algorithms. San Mateo: Morgan Kaufmann Publishers, 1991
[43] Syswerda G. Uniform crossover in genetic algorithms. In: Proceedings of the Third International Conference on Genetic Algorthms. San Mateo: Morgan Kaufmann Publishers, 1989
[44] Radcliffe N. Genetic Neural Networks on MIMD Computers, [Ph. D. ]. UK: University of Edinburgh, 1990
[45] Janilow C, Z Michalewicz. An experimental comparison of binary and floating point representations in genetic algorithms. In: Proceedings of the Fourth International Conference on Genetic Algorithms. San Marco: Morgan Kaufmann Publishers, 1991
[46] Gen M, B Liu, K Ida. Evolution program for deterministic and stochastic
optimizations. European Journal of Operational Research, 1996
[47] Gen M, B Liu, K Ida et al. Evolution program for constrained nonlinear optimization. In: Proceedings of the 16th International Conference on Computers and Industrial Engineering. Japan: Ashikaga, 1994
[48] Holland J H. Adaptation in Nature and Artificial System. The University of Michigan Press, 1975
[49] 王小平，曹立明．遗传算法——理论、应用与软件实现．西安：西安交通大学出版社，2002
[50] 仲守楠．遗传算法收敛性与编码．武汉水利电力大学学报，2000，33(1)：108～112
[51] Suzuki J. A Markov Chain Analysis in Simple Genetic Algorithms. IEEE Trans on SMS, 1995, 26(4): 655～659
[52] Kreinovich V, Quintana C, Fuentes O. Genetic Algorithms: What Fitness Scaling is Optional?. Cybernetics and Systems, 1993, 24(1): 9～36
[53] Rudoulph G C. Convergence Analysis of Canonical Genetic Algorithms. IEEE Trans on NN, 1994, 6(1): 96～101
[54] 徐川育．提高变型标准遗传算法收敛速度的混合法及其推广．信息与控制，1997，26(4)：266～271
[55] 张丰周，石继，魏永曜．应用图论及广义简约梯度法进行压力管优化设计．水利学报，1999，(1)：77～81
[56] 袁一星，赵洪宾，高健等．给水管网综合信息微机管理系统研究．中国给水排水，1994，10(6)：35～39
[57] 陈钢军．环状管网水力计算的图论方法．华侨大学学报(自然科学版)，1994，15(4)：418～422
[58] 陈为．基于AutoCAD二次开发的研究．计算机工程与应用，1999，35(1)：39～43
[59] 王钰．用VBA开发AutoCAD2000应用程序．北京：人民邮电出版社，1999
[60] 西尔伯沙茨(美)等．数据库系统概念．北京：机械工业出版社，2000
[61] 李博轩．Visual C++6.0数据库开发指南．北京：清华大学出版社，2001
[2] Amy J.Purves, A Lee Cesario. Computer applications in the water industry. J.AWWA, 1993, (4): 129～130
[3] 俞国平．给水管网优化设计的新方法——广义简约梯度法．给水排水，1988，14(5)：15～21
[4] 解可新，韩立兴，林友联．最优化方法．天津：天津大学出版社，2002
[5] 周明，孙树栋．遗传算法原理及应用．北京：国防工业出版社，1999
[6] 许仕荣，邱振华．给水管网的计算理论与电算应用．长沙：湖南大学出版社，1997
[7] 王峪飞，俞国平，彭丽娜．关于给水管道技术经济计算模型的讨论．给水排水，2001，27(3)：46～47
[8] 汪国焘．城市供水行业2000年技术进步发展规划．北京：中国建筑工业出版社，1993
[9] 周建华，赵洪宾．城市给水管网系统所面临的问题及对策．中国给水排水，2002，18(11)：30～32
[10] Morgan D.R, Goulter I.C.Optional Urban Water Distribution Design. Water Resource Research, 1985, 20(6): 642～652
[11] Kessler A, Shamir U. Decomposition Technique for Optimal Design of Water Supply Networks. Engineering Optimization, 1991, 17(1): 1～19
[12] 仲伟俊，徐南荣，沈厚才．管网系统改造优化设计问题的模型及分层分解算法．系统工程学报，1994，9(2)：11～19
[13] Mitler L G. Branch, Bound Mcthods. General Formulation and Properties. Operations Research, 1970, 18(1): 24～34
[14] 仲伟俊，徐南荣，沈厚才．供水网络系统改造的智能化计算机辅助设计．信息与控制，1995，24(6)：373～376
[15] 袁一星，陈兵，李玉华等．多水源供水管网流量分布的研究．给水排水，1998，24(5)：15～19
[16] 沈致和．“最短树”的多水源给水管网流量分配．工业用水与废水，1996，(4)：
1～4
[17] 袁亚湘，孙文瑜．最优化理论与方法．北京：科学出版社，1999
[18] 韩炜，廖振鹏．关于遗传算法收敛性的注记．地震工程与工程振动，1999，19(4)：13～16
[19] Goldberg D. Genetic Algorithms in Reareh, Optimization and Machine Learning. Addison Wesley: Reading(MA), 1989
[20] 玄光男(日)，程润伟．遗传算法与工程设计．北京：科学出版社，2000
[21] Michalewicz Z. Genetic Algorithm+Data Structure=Evolution Programs(2nd ed). New York: Spring-Verlag, 1994
[22] Holland J. Adaptation in Natural and Artificial System. Ann Arobor: Univerity of Michigan Press, 1975
[23] Goldberg D E. Optimal Initial Population Size for Binary-Coded Genetic Algorithms(M). TCGA Report, University of Alabama, 1995
[24] 李大卫．可重复自然数编码遗传算法的最优群体规模．鞍山钢铁学院学报，2000，23(6)：419～423
[25] Davis L. Adapting Operator Probabilities in Genetic Algorithms. In: Proc. of. 3rd Int. Conf. on Genetic Algorithms, Morgan Kaufmann, 1989:61～69
[26] Whitley D. et al. Genitor Ⅱ: A Distributed Genetic Algorithm. J. Expt. Ther. Intell, 1990, (2): 189～214
[27] 王煦法．遗传算法及其应用．小型微型计算机系统，1995，16(2)：59～64
[28] 王文远，Davison Mwale．提高基因算法求管网经济管径计算效率的尝试．给水排水，2000，26(2)：32～34
[29] Michalewicz Z. et al. Genetic Algorithms and Optimal Control Problem. In: Proc. of 29th IEEE Conf. on Decision and Control, 1990:1664～1666
[30] Jemikow C Z, Michalewicz Z. An Experimental Comparison of Binary and Floating Point Representation in Genetic Algorithm. In: Proc. of 4th Int. Conf. on Genetic Algorithms. Morgan Kaufmann, 1991:31～36
[31] 张美恋．基于遗传算法和单纯形法的混合优化算法．集美大学学报，2001，6(2)：106～110
[32] Fogel D. An Introduction to Simulated Evolutionary Optimization. IEEE Transactions on Neural Networks, 1994, 5: 3～14
[33] Schwefel H. Evolution and Optimum Seeking. New York: John Wiley &
Sons, 1994
[34] Grefenstette J. Proceedings of the Second International Conference on Genetic Algorithms. Hillsdale: Lawrence Erlbaum Associates(NJ), 1995
[35] Kim J H, H Myung. A two-phase evolutionary programming for general constrained optimization problem. In: Proc. of the Fifth Conference on Evolutionary Programming. San Diego: 1996
[36] Eshelman L J. Proceedings of Sixth International Conference on Genetic Algorithms. San Francisco: Morgan Kaufmann Publishers, 1995
[37] Myung H, JH Kim. Hybrid evolutionary programming for heavily constraimed problems. Bio-Systems, 1996, 38: 29～43
[38] Fogel D. Proceedings of the First IEEE Conference on Evolutionary Computation. Orlando: IEEE Press, 1994
[39] McDonnell J, R Reynolds, D Fogel. Evolutionary Programming Ⅳ. Cambridge: MIT Press, 1995
[40] Michalewicz Z, D Dasgupta, R G Le Riche et al. Evolutionary algorithms for Industrial Engineering problems. International Journal of Computers and Industrial Engineering, 1996, 30(4)
[41] Davis L. Handbook of Genetic Alogrithms. New York: Van Nostrand Reinhold, 1991
[42] Spears W, K De Jong. On the virtues of parameterized uniform cross-over. In: Proceedings of the Fourth International Conference on Genetic Algorithms. San Mateo: Morgan Kaufmann Publishers, 1991
[43] Syswerda G. Uniform crossover in genetic algorithms. In: Proceedings of the Third International Conference on Genetic Algorthms. San Mateo: Morgan Kaufmann Publishers, 1989
[44] Radcliffe N. Genetic Neural Networks on MIMD Computers, [Ph. D. ]. UK: University of Edinburgh, 1990
[45] Janilow C, Z Michalewicz. An experimental comparison of binary and floating point representations in genetic algorithms. In: Proceedings of the Fourth International Conference on Genetic Algorithms. San Marco: Morgan Kaufmann Publishers, 1991
[46] Gen M, B Liu, K Ida. Evolution program for deterministic and stochastic
optimizations. European Journal of Operational Research, 1996
[47] Gen M, B Liu, K Ida et al. Evolution program for constrained nonlinear optimization. In: Proceedings of the 16th International Conference on Computers and Industrial Engineering. Japan: Ashikaga, 1994
[48] Holland J H. Adaptation in Nature and Artificial System. The University of Michigan Press, 1975
[49] 王小平，曹立明．遗传算法——理论、应用与软件实现．西安：西安交通大学出版社，2002
[50] 仲守楠．遗传算法收敛性与编码．武汉水利电力大学学报，2000，33(1)：108～112
[51] Suzuki J. A Markov Chain Analysis in Simple Genetic Algorithms. IEEE Trans on SMS, 1995, 26(4): 655～659
[52] Kreinovich V, Quintana C, Fuentes O. Genetic Algorithms: What Fitness Scaling is Optional?. Cybernetics and Systems, 1993, 24(1): 9～36
[53] Rudoulph G C. Convergence Analysis of Canonical Genetic Algorithms. IEEE Trans on NN, 1994, 6(1): 96～101
[54] 徐川育．提高变型标准遗传算法收敛速度的混合法及其推广．信息与控制，1997，26(4)：266～271
[55] 张丰周，石继，魏永曜．应用图论及广义简约梯度法进行压力管优化设计．水利学报，1999，(1)：77～81
[56] 袁一星，赵洪宾，高健等．给水管网综合信息微机管理系统研究．中国给水排水，1994，10(6)：35～39
[57] 陈钢军．环状管网水力计算的图论方法．华侨大学学报(自然科学版)，1994，15(4)：418～422
[58] 陈为．基于AutoCAD二次开发的研究．计算机工程与应用，1999，35(1)：39～43
[59] 王钰．用VBA开发AutoCAD2000应用程序．北京：人民邮电出版社，1999
[60] 西尔伯沙茨(美)等．数据库系统概念．北京：机械工业出版社，2000
[61] 李博轩．Visual C++6.0数据库开发指南．北京：清华大学出版社，2001
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |