物流运输网络多目标最短路问题的模糊满意解

运筹与管理 ›› 2014, Vol. 23 ›› Issue (5): 55-61.

物流运输网络多目标最短路问题的模糊满意解

韩世莲¹, 刘新旺²

1.南京财经大学营销与物流学院,江苏南京 210046;
2.东南大学经济管理学院,江苏南京 210096

收稿日期:2013-04-01 出版日期:2021-05-25
作者简介:韩世莲(1970-),女,博士,副教授,研究方向:物流系统决策;刘新旺(1968-),男,教授,博士生导师,研究方向:模糊决策。
基金资助:
国家自然科学基金资助项目(71171048,71371049);教育部人文社会科学研究规划基金项目(13YJA630025);教育部留学回国人员科研启动基金资助项目;江苏省高校优势学科建设工程及南京财经大学重点预研究项目(A2011002)

Fuzzy Optimal Solutions for Multiobjective Shortest Path Problems in the Logistics Transportation Network

HAN Shi-lian¹, LIU Xin-wang²

1. School of Marketing & Logistics,Nan Jing University of Finance & Economics, Nanjing 210046,China;
2. School of Economics and Management, Southeast University, Nanjing 210096, China

Received:2013-04-01 Online:2021-05-25

摘要/Abstract

摘要： 本文对物流运输网络多目标最短路问题进行了研究。提出了一种求解多目标最短路问题的目标集成方法和对集成后目标函数求解的扩展标号法。在将多目标转化为单目标时,综合考虑了每个目标的边缘评价和所有目标的整体评价因素,通过对每个目标的权重分配将决策者的偏好充分体现到决策过程中,采用广义的模糊目标集成算子形成了相应的折衷规划模型。最后,通过实例对本文所提方法进行了说明。

关键词: 物流管理, 模糊满意解, 扩展标号法, 多目标最短路问题.

Abstract: The paper concentrates on the multiobjective shortest path problem in the logistics transportation network. An objective aggregation method with the fuzzy compromise programming technique and an extended label correcting method to solve the aggregated objective are proposed. In the process of aggregating multiple objectives to a single one, the edge evaluation for each objective and the overall evaluation for all the objectives are considered. By assigning the weights to each objective, the decision maker's preference information can be integrated in this aggregation process, and the fuzzy compromise solution can be got with the generic aggregation method. Finally, a numerical example shows the solution process of the proposed approach.

Key words: logistics management, fuzzy optimal solution, extended label correcting method, multi-objective shortest path problem.

中图分类号:

韩世莲, 刘新旺. 物流运输网络多目标最短路问题的模糊满意解[J]. 运筹与管理, 2014, 23(5): 55-61.

HAN Shi-lian, LIU Xin-wang. Fuzzy Optimal Solutions for Multiobjective Shortest Path Problems in the Logistics Transportation Network[J]. Operations Research and Management Science, 2014, 23(5): 55-61.

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