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考虑设施深度的过道布置问题及改进烟花算法求解方法
引用本文:刘思璐,张则强,管超,龚举华.考虑设施深度的过道布置问题及改进烟花算法求解方法[J].控制与决策,2020,35(1):45-54.
作者姓名:刘思璐  张则强  管超  龚举华
作者单位:西南交通大学机械工程学院,成都610031;轨道交通运维技术与装备四川省重点实验室,成都610031
基金项目:国家自然科学基金项目(51205328,51675450);教育部人文社会科学研究青年基金项目(18YJC630255);四川省科技计划项目(2019YFG0285).
摘    要:针对过道布置问题中忽略设施深度及物流交互点置于过道边线的问题,结合实际布局活动对过道布置问题进行拓展,构建考虑设施深度的过道布置问题的混合整数规划模型,并提出一种改进烟花算法.该算法采用2-opt邻域构造方法对爆炸操作进行离散化处理;设置搜索深度并执行两点变异操作,实现变邻域搜索;通过贪婪选择方法更新种群以记忆精英解.为改进算法,引入混沌映射初始化烟花种群和设置阈值以加速算法寻优.通过对比数学规划方法与所提出算法的求解结果,验证了模型的有效性和所提出算法的求解优势.最后,通过不同算法的对比实验表明,改进烟花算法在寻优精度、收敛效率和稳定性方面均有明显优势.

关 键 词:过道布置问题  烟花算法  MIP数学模型  设施布局

Improved fireworks algorithm for the corridor allocation problem with facility depth
LIU Si-lu,ZHANG Ze-qiang,GUAN Chao and GONG Ju-hua.Improved fireworks algorithm for the corridor allocation problem with facility depth[J].Control and Decision,2020,35(1):45-54.
Authors:LIU Si-lu  ZHANG Ze-qiang  GUAN Chao and GONG Ju-hua
Affiliation:1. School of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,China;2. Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province,Chengdu 610031,China,1. School of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,China;2. Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province,Chengdu 610031,China,1. School of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,China;2. Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province,Chengdu 610031,China and 1. School of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,China;2. Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province,Chengdu 610031,China
Abstract:In view of the shortcomings in the existing research on the corridor allocation problem (CAP), in which the facility depth is always ignored and the logistics interaction points are always placed on the side line of the corridor, the CAP is extended according to the actual layout activities. A mixed integer programming model is constructed and an improved fireworks algorithm is proposed. In the improved algorithm, the explosion operation is discretized through a neighborhood construction method. The search depth and the two point mutation operation are set up to realize the variable neighborhood search. The greedy selection method is applied to update the population to memorize the elite solution. Furthermore, chaos mapping is introduced to initialize the fireworks population, and the threshold is set under the premise of high quality solution to accelerate optimization. Through comparing the results of mathematical programming with the proposed algorithm, the validity of the proposed model and the advantages of the presented algorithm are verified. Finally, the comparison experiments of different algorithms show that the improved fireworks algorithm has obvious advantages in optimization accuracy, convergence efficiency and stability.
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