基于启发式算法的应急物资储备点选址模型研究  

Study on the Location Model of Emergency Material Reserve Point Based on Heuristic Algorithm

作　　者：裴姝艺 叶晓飞[1] 洪钢 周义雄 郑彭军[1] PEI Shuyi;YE Xiaofei;HONG Gang;ZHOU Yixiong;ZHENG Pengjun(School of Maritime and Transportation,Ningbo University,Ningbo 315211,China;Ningbo Zhongtong Logistics Group Co.,Ltd.,Ningbo 315211,China)

机构地区：[1]宁波大学海运学院,浙江宁波315211 [2]宁波中通物流集团有限公司,浙江宁波315211

出　　处：《物流科技》2023年第22期1-6,11,共7页Logistics Sci-Tech

基　　金：宁波市交通运输科技计划项目“突发事件下应急物资智能仓配一体化调配关键技术研究”(202214)。

摘　　要：应急物资储备点选址是应急物资配送网络优化中的一项重要任务,能够有效提高救援物资配送的效率。由于精确技术有限,无法解决规模较大和NP难(多项式复杂程度的非确定性问题)的问题,为了尽可能逼近最优解,得到一个相对优解,因此需要使用启发式算法进行计算。为寻找合适算法以更好地进行应急物资储备点选址,文章首先构建了考虑储备点最大容量限制的成本最小化模型,然后使用启发式模拟退火算法和启发式遗传算法求解,对四川省进行算例分析,比较两个启发式算法所得解的精确程度和收敛情况。结果表明,模型最优解为2849.2375万元,并且模拟退火算法比遗传算法的所得解可靠性更强、运算速度更快、收敛情况更稳定。The location selection of emergency material reserve points is an important task in the optimization of emergency material distribution network,which can effectively improve the efficiency of rescue material distribution.Due to limited precision technology,it is impossible to solve large-scale and NP difficult(non deterministic problems with polynomial complexity)problems.In order to approach the optimal solution as much as possible and obtain a relatively optimal solution,heuristic algorithms need to be used for calculation.And in order to find suitable algorithms for better selecting emergency material reserve points,a cost minimization model considering the maximum capacity limit of the reserve points is first constructed.Then,a heuristic simulated annealing algorithm and a heuristic genetic algorithm are used to solve the problem.A case study is conducted in Sichuan Province to compare the accuracy and convergence of the solutions obtained by the two heuristic algorithms.The results show that the optimal solution of the model is 28.492375 million yuan,and the simulated annealing algorithm has stronger reliability,faster operation speed,and more stable convergence than the genetic algorithm.

关 键 词：选址 数学模型 模拟退火算法 遗传算法 

分 类 号：F259.27[经济管理—国民经济]