基于数学规划的救援物资分配优化模型及其求解算法综述

doi:10.11772/j.issn.1001-9081.2020010102

计算机应用 ›› 2020, Vol. 40 ›› Issue (8): 2398-2409.DOI: 10.11772/j.issn.1001-9081.2020010102

• 应用前沿、交叉与综合 • 上一篇下一篇

基于数学规划的救援物资分配优化模型及其求解算法综述

曹策俊¹, 高学鸿²

1. 重庆工商大学商务策划学院, 重庆 400067;
2. 釜山大学工业工程系, 釜山 609-735, 韩国

收稿日期:2020-02-07 修回日期:2020-04-09 出版日期:2020-08-10 发布日期:2020-04-16
通讯作者: 曹策俊(1990-),男,四川南充人,讲师,博士,主要研究方向:应急资源配置、智能算法,caocejun0601@tju.edu.cn
作者简介:高学鸿(1990-),男,河南焦作人,博士研究生,主要研究方向:灾害运作管理、决策建模、智能算法。
基金资助:
国家自然科学基金资助项目（71904021）；重庆市社会科学规划项目（2019QNGL27）；重庆市教委科学技术研究计划项目（KJQN201900830）；重庆工商大学校内科研项目（1951025）；四川省科技厅国际科技创新合作项目（20GJHZ0039）；重庆工商大学引进高层次人才科研启动项目（1955011）。

Overview of relief distribution optimization models based on mathematical programming and their solving algorithms

CAO Cejun¹, GAO Xuehong²

1. School of Business Planning, Chongqing Technology and Business University, Chongqing 400067, China;
2. Department of Industrial Engineering, Pusan National University, Busan 609-735, Korea

Received:2020-02-07 Revised:2020-04-09 Online:2020-08-10 Published:2020-04-16
Supported by:
This work is partially supported by the National Natural Science Foundation of China (71904021), the Social Science Planning Project in Chongqing (2019QNGL27), the Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN201900830), the Research Project in Chongqing Technology and Business University (1951025), the International Science and Technology Innovation Cooperation Project of Sichuan Science and Technology Department (20GJHZ0039), the Scientific Research Start-up Foundation for Introduction of Advanced Talents in Chongqing Technology and Business University (1955011).

摘要/Abstract

摘要： 为了提高救援物资利用率、减少各种损失与缓解幸存者痛苦，如何采用数学规划方法优化救援物资分配策略是当前亟待解决的重要问题。根据目标数量和“府际”关系两个准则梳理了救援物资分配数学规划模型的研究现状，综述了救援物资分配优化模型求解算法的研究进展，总结并指出了救援物资分配优化问题未来的研究方向。研究表明：构建救援物资分配优化支撑框架是必要的，而且救援物资分配优化模型从单目标规划向多目标规划延伸，救援物资分配问题的研究视角从横向“府际”关系向纵向“府际”关系转变，从确定条件下的救援物资分配优化问题向不确定条件下的救援物资分配优化问题发展，从传统的救援物资分配优化问题向融入可持续发展理念的救援物资分配问题转变，从精确算法向启发式算法设计解法发展，将大数据、数字孪生、区块链等新信息与通信技术（ICT）应用于构建救援物资分配模型都是必要的。

关键词: 救援物资分配, 数学规划, 目标数量, “府际”关系

Abstract: To improve the utilization of relief, reduce various losses and alleviate the suffering of survivors, how to use mathematical programming methods to optimize relief distribution strategy is a critical issue urgent to be solved currently. The current status of mathematical programming models for relief distribution was analyzed according to the criteria of objective quantity and intergovernmental relationships. An overview of the algorithms to solve the relief distribution optimization models was conducted. The future directions of the relief distribution optimization problem were summarized and pointed out. Research indicates that the establishment of the optimization support framework of relief distribution is necessary. And it is necessary that:the relief distribution optimization model is extended from single-objective programming to multiple-objective programming, the research viewpoint of relief distribution issue is changed from horizontal intergovernmental relationship to vertical one, the development from the certain condition based relief distribution optimization problem to the uncertain condition based one, the change from traditional relief distribution problem to the one with sustainable development idea, the design of solutions from using exact algorithm to using heuristic one, and applying new Information and Communications Technology (ICT) such as big data, digital twin and blockchain to develop relief distribution models.

Key words: relief distribution, mathematical programming, objective quantity, intergovernmental relationship

中图分类号:

TP399
X931

曹策俊, 高学鸿. 基于数学规划的救援物资分配优化模型及其求解算法综述[J]. 计算机应用, 2020, 40(8): 2398-2409.

CAO Cejun, GAO Xuehong. Overview of relief distribution optimization models based on mathematical programming and their solving algorithms[J]. Journal of Computer Applications, 2020, 40(8): 2398-2409.

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基于数学规划的救援物资分配优化模型及其求解算法综述

Overview of relief distribution optimization models based on mathematical programming and their solving algorithms

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