易燃品仓库群三维移动智慧巡检路径优化
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摘要
针对多个易燃品仓库的群巡检的智能滑块路径寻优问题,提出贪心遗传混合式路径优化算法,该算法将贪心策略融入到遗传算法操作过程,用作指导遗传选择操作进行搜索。首先建立仓库群巡检目标分配数学模型,其次设计一种基于贪心遗传混合式算法的三维移动巡检系统。对稀土金属库的规模不同的巡检点进行仿真,与常规的遗传算法和粒子群算法相比,平均巡检路径长度减少了15. 2%,对103个巡检点巡检路径长度减少了6. 1%.对1层库41个巡检点、2层库的51个巡检点、33层库的75个巡检点仿真结果表明,该方法避免了遗传算法的早熟问题,无论巡检的收敛速度还是巡检的最短路径均有明显改善。为保证安全,可在危险品大物资仓库推广使用,具有一定的应用价值和安全示范作用。
Aim at flammable goods warehouse,a greedy genetic hybrid path optimization algorithm is proposed with Intelligent slider to solve the problem of searching the optimal path of warehouse group.The greedy strategy is integrated into the genetic algorithm,which is used as a guide for genetic selection in this algorithm. Firstly,the mathematical model for the distribution of warehouse inspection target is established. Secondly,a 3 D mobile inspection system based on greedy genetic hybrid algorithm is designed to solve this problem. Next,different scale inspection points of rare earth metal libraries are simulated. Compared with the conventional genetic algorithm and the particle swarm algorithm,the average inspection path length is reduced by 15. 2%,and the inspection path length of 103 inspection points is reduced by 6. 1%. The simulation results of 41 inspection points in the 1 st floor library,51 inspection points in the 2 layer library,and 75 inspection points in the 33 layer library show that the method can avoid the premature convergence,and regarding both the convergence speed of the inspection and the shortest path of the inspection,there is a significant improvement. The method has strong operability and high efficiency. It can be widely used in the warehouse group,which has certain application value and demonstration function for safety.
Aim at flammable goods warehouse,a greedy genetic hybrid path optimization algorithm is proposed with Intelligent slider to solve the problem of searching the optimal path of warehouse group.The greedy strategy is integrated into the genetic algorithm,which is used as a guide for genetic selection in this algorithm. Firstly,the mathematical model for the distribution of warehouse inspection target is established. Secondly,a 3 D mobile inspection system based on greedy genetic hybrid algorithm is designed to solve this problem. Next,different scale inspection points of rare earth metal libraries are simulated. Compared with the conventional genetic algorithm and the particle swarm algorithm,the average inspection path length is reduced by 15. 2%,and the inspection path length of 103 inspection points is reduced by 6. 1%. The simulation results of 41 inspection points in the 1 st floor library,51 inspection points in the 2 layer library,and 75 inspection points in the 33 layer library show that the method can avoid the premature convergence,and regarding both the convergence speed of the inspection and the shortest path of the inspection,there is a significant improvement. The method has strong operability and high efficiency. It can be widely used in the warehouse group,which has certain application value and demonstration function for safety.
引文
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[23] Theofania Tsironi,Peter Ronnow,Marianna Giannoglou.Developing suitable smart TTI labels to match specific monitoring requirements:the case of Vibrio spp. growth during transportation of oysters[J]. Food Control,2016,41(6):51-56.
[24] Holden R,Xu B,Greening P,et al. Towards a common measure of greenhouse gas related logistics activity using data envelopment analysis[J]. Transportation Research Part A,2016,6(1):105-119.
[25] Behmel S,Damour M,Ludwig R,et al. Water quality monitoring strategies:a review and future perspectives[J]. Science of the Total Environment,2016,235(6):1312-1329.
[2] Rey,Tseng,Chun Pin. Hazard management and risk design by optimal statistical analysis[J]. Journal of Natural Hazards,2012,64:1707-1716.
[3]丁柏铨.浅议重大公共危机事件中新闻发言人的发言与舆论的关系[J].新闻大学,2013(4):52-56.DING Bo-quan. The relationship between the speeches of the spokespersons and the public opinions in the major public crisis events[J]. Journalism University,2013(4):52-56.
[4]赵东风,韩丰磊,徐建军.警惕化学品“活性”危害[J].劳动保护,2016(11):104-107.ZHAO Dong-feng,HAN Feng-lei,XU Jian-jun. Be wary of chemical “activity” hazards[J]. Labor Protection,2016(11):104-107.
[5] LU Gang,HAO Ping. Recognition of CAPTCHA based on weighted template matching and supervised learning[J]. Computer and Modernization,2010(12):40-43.
[6] Hassanzadeh R,Mahdavi I,Mahdavi-Amiri N,et al. A genetic algorithm forsolving fuzzy shortest path problems with mixed fuzzy arc lengths[J]. Mathematical and Computer Modelling,2013,57(1):84-99.
[7] Tanackov Ilija,Jankovi8,Zdenko; Sremac,Sini2a,et al.Risk distribution of dangerous goods in logistics subsystems[J]. Journal of Loss Prevention in the Process Industries,2018,54(3):373-383.
[8] Layeb Abdesslem,Benayad Zeyneb. A novel firefly algorithm based ant colony optimization for solving combinatorial optimization problems[J]. International Journal of Computer Science and Applications,2014,11(2):19-37.
[9] Kawata Yuko,Azuma Hiroyuki. Some approaches for optimizing CO2storage system with water production in a heterogeneous reservoir using particle swarm optimization algorithm[J]. Energy Procedia,2017,114(1):4775-4786.
[10]李依桐,林燕.基于混合粒子群算法的云计算任务调度研究[J].计算技术与自动化,2014,33(1):73-77.LI Yi-tong,LIN Yan. Research on cloud computing task scheduling based on hybrid particle swarm optimization[J]. Computing Technology and Automation,2014,33(1):73-77.
[11] Asta Shahriar,zcan Ender. A tensor analysis improved genetic algorithm for online bin packing[C]//Proceedings of the 2015 Genetic and Evolutionary Computation Conference,2015(11):799-806
[12] LI Jian-qiang,ZHANG Shen-peng,YANG Lei. Accurate RFID localization algorithm with particle swarm optimization based on reference tags[J]. Intelligent Fuzzy System,2016,31(5):2697-2706.
[13]蔡益红.多特征融合的道路车辆检测方法[J].计算技术与自动化,2013,33(1):98-102.CAI Yi-hong. Multi-feature fusion road vehicle detection method[J]. Computing Technology and Automation,2013,33(1):98-102.
[14]田子建,李宗伟.基于电磁波及超声波联合测距的井下定位方法[J].北京理工大学学报,2014,34(5):26-29.TIAN Zi-jian,LI Zong-wei. Downhole positioning method based on electromagnetic wave and ultrasonic combined ranging[J]. Journal of Beijing Institute of Technology,2014,34(5):26-29.
[15]王于丁,杨家海,徐聪,等.云计算访问控制技术研究综述[J].软件学报,2015,25(5):1129-1149.WANG Yu-ding,YANG Jia-hai,XU Cong,et al. A survey of cloud computing access control technology[J].Journal of Software,2015,25(5):1129-1149.
[16]陈显,侯媛彬,宋柏佑.等.基于步进电机的小型三维运动物流系统设计[J].西安科技大学学报,2016,36(6):868-874.CHEN Xian,HOU Yuan-bin,SONG Bai-you,et al. Design of small 3D movement logistics system based on stepper motors[J]. Journal of Xi’an University of Science and Technology,2016,36(6):868-874.
[17]沈捷.快消品企业仓储管理系统的设计与实施[D].南昌:江西财经大学,2017.SHEN Jie. Design and implementation of storage management system for fast consumption enterprises[D].Nanchang:Jiangxi University of Finance and Economics,2017.
[18]林以成.基于GPRS技术的仓库监控系统[J].仪表技术与传感器,2018(8):103-104.LIN Yi-cheng. Warehouse monitoring system based on GPRS technology[J]. Instrument Technique and Sensor,2018(8):103-104.
[19]马殷元.物流装备控制和监控系统关键技术研究[D].兰州:兰州交通大学,2017.MA Yin-yuan. Research on key technologies of logistics equipment control and monitoring system[D]. Lanzhou:Lanzhou Jiaotong University,2017.
[20]毕文俊.电信行业数据仓库数据质量管理系统设计与实现[D].北京:中国科学院大学,2017.BI Wen-jun. Design and implementation of data quality management system for data warehouse in telecom industry[D]. Beijing:University of Chinese Academy of Sciences,2017.
[21] Raitis Apsalons,Gennady Gromov. Methodology of evaluation of the impact of picking area location on the total costs of warehouse[J]. Transport and Telecommunication Journal,2017,31(10):332-344.
[22]李志宾.自动化立体仓库调度优化问题研究[D].太原:中北大学,2017.LI Zhi-bin. Research on the scheduling optimization of automated stereo warehouse[D]. Taiyuan:North Central University,2017.
[23] Theofania Tsironi,Peter Ronnow,Marianna Giannoglou.Developing suitable smart TTI labels to match specific monitoring requirements:the case of Vibrio spp. growth during transportation of oysters[J]. Food Control,2016,41(6):51-56.
[24] Holden R,Xu B,Greening P,et al. Towards a common measure of greenhouse gas related logistics activity using data envelopment analysis[J]. Transportation Research Part A,2016,6(1):105-119.
[25] Behmel S,Damour M,Ludwig R,et al. Water quality monitoring strategies:a review and future perspectives[J]. Science of the Total Environment,2016,235(6):1312-1329.