Improved Wolf Pack Algorithm for Distribution of Molds on Molds Table

doi:10.16182/j.issn1004731x.joss.19-0262

Abstract

Abstract: In order to solve the problem of the distribution of molds on the mold table in the production process of concrete prefabricated components, a method combining Bottom-Left Algorithm (BLA) and Improved Wolf Pack Algorithm (IWPA) is proposed. Improved Wolf Pack Algorithm is for optimizing the order of upper line and the mold used for each member is sequentially assigned to the mold table according to the upper line. BLA is used to determine the direction and position of the molds on the molds table. The WPA safari behavior is improved by introducing Levi's flying ideas and the Hamming distance-based wolf pack dynamic update mechanism is used to improve the Wolf Pack Algorithm. The wolf pack diversity is enriched and the search ability of WPA in the solution space is enhanced. An example test is carried out to verify the effectiveness of the method.

Key words: wolf pack algorithm, concrete prefabricated component, distribution of molds on the mold table, levy flights, hamming distance

CLC Number:

Han Zhonghua, Liu Yuehan, Li Man, Sun Liangliang, Zheng Hongzhi. Improved Wolf Pack Algorithm for Distribution of Molds on Molds Table[J]. Journal of System Simulation, 2021, 33(1): 127-140.

References

[1] 李永敢. 装配式建筑预制混凝土构件自动化生产线设计配置技术[J]. 施工技术, 2018, 47(4): 47-51.
Li Yonggan.Design Configuration Technology of Automatic Production Line for Prefabricated Concrete Member of Precast Building[J]. Construction Technology, 2018, 47(4): 47-51.
[2] 张晓薇. 装配式混凝土小型构件自动化生产施工技术[J]. 建筑安全, 2019, 34(2): 41-44.
Ma Xiaowei.Construction Technology for Automation Production of Small Assembled Concrete Components[J]. Construction Safety, 2019, 34(2): 41-44.
[3] 廖礼平. 绿色装配式建筑发展现状及策略[J]. 企业经济, 2019, 38(12): 139-146.
Liao Liping.Development status and strategy of green prefabricated building[J]. Enterprise Economy, 2019, 38(12): 139-146.
[4] 李上志, 金伟. 建筑预制构件的工业化生产[J]. 四川建筑, 2018, 38(3): 210-211.
Li Shangzhi, Jin Wei.Industrial Production of Building Prefabricated Components[J]. Sichuan Architecture, 2018, 38(3): 210-211.
[5] 谢思聪, 陈小波. 基于多层编码遗传算法的两阶段装配式建筑预制构件生产调度优化[J]. 工程管理学报, 2018, 32(1): 18-22.
Xie Sicong, Chen Xiaobo.Two Phase Job-shop Scheduling Optimization for Prefabricated Construction Projects Based on Multilayer Coding Genetic Algorithm[J]. Journal of Engineering Management, 2018, 32(1): 18-22.
[6] 朱敏涛. 可扩展组合式预制构件数字化生产线的研究[J]. 建筑施工, 2018, 40(6): 1026-1028.
Zhu Mintao, Research on Digitalized Production Line of Extendable Modular Precast Components[J]. Building Construction, 2018, 40(6): 1026-1028.
[7] 王中原, 陈小波. 基于遗传算法的板类预制构件生产中的模具排布优化研究[J]. 工程管理学报, 2019, 33(1): 45-49.
Wang Zhongyuan, Chen Xiaobo.An Optimization Analysis of Prefabricated Component Production Mold Arrangement Based on Genetic Algorithm[J]. Journal of Engineering Management, 2019, 33(1): 45-49.
[8] 马龙, 卢才武, 顾清华. 求解离散优化问题的元胞量子狼群演化算法[J]. 智能系统学报, 2018, 13(5): 716-727.
Ma Long, Lu Caiwu, Gu Qinghua.Cellular and Quantum-behaved Wolf Pack Evolutionary Algorithm for Solving Discrete Optimization Problems[J]. CAAI Transactions on Intelligent Systems, 2018, 13(5): 716-727.
[9] 黄海松, 任竹鹏, 魏建安. 改进狼群算法求解旅行商问题[J]. 计算机应用研究, 2019, 36(12): 3644-3646.
Huang Haisong, Ren Zhupeng, Wei Jianan.Improved Wolf Group Algorithm for Solving Traveling Salesman Problem[J]. Application Research of Computers, 2019, 36(12): 3644-3646.
[10] 吴虎胜, 张凤鸣, 吴庐山. 一种新的群体智能算法—狼群算法[J]. 系统工程与电子技术, 2013, 35(11): 2430-2438.
Wu Husheng, Zhang Fengming, Wu Lushan.New Swarm Intelligence Algorithm-Wolf Pack Algorithm[J]. Systems Engineering and Electronics, 2013, 35(11): 2430-2438.
[11] 吴虎胜, 张凤鸣, 李浩, 等. 求解TSP问题的离散狼群算法[J]. 控制与决策, 2015, 30(10): 1861-1867.
Wu Husheng, Zhang Fengming, Li Hao, et al.Discrete Wolf Pack Algorithm for Traveling Salesman Problem[J]. Control and Decision, 2015, 30(10): 1861-1867.
[12] Hui X B, Guo Q, Wu P P, et al.An Improved Wolf Pack Algorithm[J]. Control and Decision (S1001-0920), 2017, 32(7): 1163-1172.
[13] Chen X Y, Tang C J, Wang J, et al.Improved Wolf Pack Algorithm Based on Differential Evolution Elite Set[J]. IEICE Transactions on Information and Systems (S1745-1361), 2018, 101(7): 1946-1949.
[14] 王学武, 严益鑫, 顾幸生. 基于莱维飞行粒子群算法的焊接机器人路径规划[J]. 控制与决策, 2017, 32(2): 373-377.
Wang Xuewu, Yan Yixin, Gu Xingsheng.Welding Robot Path Planning Based on Levy-PSO[J]. Control and Decision, 2017, 32(2): 373-377.
[15] 刘晓龙, 宁芊, 赵成萍. 基于莱维飞行的鸟群优化算法[J]. 计算机测量与控制, 2016, 24(12): 194-197.
Liu Xiaolong, Ning Qian, Zhao Chengping.Bird Swarm Algorithm Based on Levy Flight[J]. Computer Measurement & Control, 2016, 24(12): 194-197.
[16] Ehsan V.A Cuckoo Search Algorithm by Levy Flights for Solving Reliability Redundancy Allocation Problems[J]. Engineering Optimization (S1029-0273), 2013, 45(11): 1273-1286.
[17] Mantegna R N.Fast, Accurate Algorithm for Numerical Simulation of Lévy Stable Stochastic Processes[J]. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics (S1063-651X), 1994, 49(5): 4677-4683.
[18] 丛培强, 李梁, 陈亚茹. 基于汉明距离与免疫思想的粒子群算法[J]. 重庆理工大学学报(自然科学), 2019, 33(4): 122-127.
Cong Peiqiang, Li Liang, Chen Yaru.Particle Swarm Optimization Algorithm Based on Optimization Hamming Distance and Immune Thought[J]. Journal of Chongqing University of Technology (Natural Science), 2019, 33(4): 122-127.