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考虑备灾的双层规划应急资源调度选址—路径优化模型与算法
引用本文:万孟然,叶春明,董 君,赵灵玮,郭 静. 考虑备灾的双层规划应急资源调度选址—路径优化模型与算法[J]. 计算机应用研究, 2021, 38(10): 2961-2967. DOI: 10.19734/j.issn.1001-3695.2021.03.0079
作者姓名:万孟然  叶春明  董 君  赵灵玮  郭 静
作者单位:上海理工大学 管理学院,上海200093;上海理工大学 管理学院,上海200093;河南工学院 管理学院,河南 新乡453000
基金项目:上海市科委“科技创新行动计划”软科学重点项目(20692104300);国家自然科学基金资助项目(71840003);上海理工大学科技发展项目(2018KJFZ043)
摘    要:备灾措施可以为救灾做准备,为确保灾后应急物资可以及时高效地到达灾区,提出了考虑备灾的双层规划应急资源调度选址—路径优化模型,上层规划以供应站建设和运营总成本最低为目标,而下层规划以配送路径成本最小化为目标.设计了一种改进的双层樽海鞘遗传算法求解该问题,结合迭代划分的概念更新领导者位置,采用自然指数惯性权值策略修正控制因子,利用混沌映射更新追随者位置,采用田口分析方法获取参数合理取值.最后,通过使用双层樽海鞘遗传算法与遗传粒子群混合算法、粒子群优化算法、免疫优化算法对OR-Library中的LRP(location-routing problem,LRP)数据集进行求解和对比分析,验证了所提模型和算法的可行性和有效性.

关 键 词:选址—路径  应急资源调度  双层规划  双层樽海鞘遗传算法
收稿时间:2021-03-30
修稿时间:2021-09-15

Bi-level programming location-routing optimization model and algorithm for emergency resource scheduling considering preparedness
Wan Mengran,Ye Chunming,Dong Jun,Zhao Lingwei and Guo Jing. Bi-level programming location-routing optimization model and algorithm for emergency resource scheduling considering preparedness[J]. Application Research of Computers, 2021, 38(10): 2961-2967. DOI: 10.19734/j.issn.1001-3695.2021.03.0079
Authors:Wan Mengran  Ye Chunming  Dong Jun  Zhao Lingwei  Guo Jing
Affiliation:Business School,University of Shanghai for Science and Technology,,,,
Abstract:Disaster preparedness measures can prepare for disaster relief to ensure that emergency supplies can reach the disa-ster area in a timely and effective manner. This paper proposed a bi-level programming emergency resource scheduling location-routing model with considering preparedness(BLERSLR-P). In the model, the upper level aimed to minimize the total cost of supply station construction and operation, while the lower level aimed to minimize the cost of distribution route. This paper designed an improved bi-level salp swarm genetic algorithm(BLSSAGA) to solve this problem, combined the concept of iterative division to update the leader position, used the natural exponential inertia weight strategy to modify the control factor, used the chaotic map to update the follower position, and used Taguchi analysis to obtain reasonable values of parameters. Finally, this paper used bi-level salp swarm genetic algorithm(BLSSAGA) and genetic particle swarm optimization algorithm(GAPSO), particle swarm optimization algorithm(PSO), and immune optimization algorithm(IA) to solve and compare and analyze the LRP data set in OR-Library, which verified the feasibility and effectiveness of the proposed model and algorithm.
Keywords:location-routing   emergency resource scheduling   bi-level programming   BLSSAGA
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