Emergency material scheduling optimization model and algorithms:A review

论文摘要

In the emergency management of disruptions,efficient emergency material scheduling（EMS） is a key factor to save people’s lives and reduce loss.Based on the literature of EMS and related areas in recent years,the research was summarized from two aspects of EMS optimization model and algorithms.It is concluded that the EMS optimization models mainly aim at the shortest time,shortest distance,minimum cost,maximum satisfaction and fairness,etc.The constraints usually include the quantity of supply depots,relief supply and vehicles,the types of commodities,the road network conditions,the budgets and the demand forecast of emergency materials.Multi-objective model is more complex and it usually considers more than one objective.To find the optimized solution,the multiobjective model with complex constraints needs more efficient algorithms.The existing algorithms,including mathematic algorithm and heuristic algorithm,have been categorized.For NP-hard（non-deterministic polynomial hard） problems,heuristic algorithms should be designed,which mainly include genetic algorithm（GA）,ant colony optimization（ACO）,particle swarm optimization（PSO）,etc.Based on the characteristics of the optimization model and various algorithms,appropriate algorithm or tools should be chosen and designed to obtain the optimized solution of EMS model.Finally,the development trends of EMS optimization model and algorithm in the future are proposed.

论文目录

文章来源

类型: 期刊论文

作者: Hui Hu,Jing He,Xiongfei He,Wanli Yang,Jing Nie,Bin Ran

来源: Journal of Traffic and Transportation Engineering(English Edition) 2019年05期

年度: 2019

分类: 工程科技Ⅱ辑,工程科技Ⅰ辑,经济与管理科学

专业: 安全科学与灾害防治,公路与水路运输,宏观经济管理与可持续发展

单位: School of Automobile,Chang'an University,School of Civil and Environmental Engineering,University of Wisconsin at Madison

基金: supported by the China Fundamental Research Funds for the Central Universities under Grant300102228402 and 3100102229103,China Xi’an Social Science Planning Fund under Grant 19Z73,Shaanxi Natural Science Foundation of China under Grant 2019JLP-07,the China Innovation and Entrepreneurship Training Program for College Students under Grant 20191071245

分类号: X4;U116;F251

页码: 441-454

总页数: 14

文件大小: 2270K

下载量: 39

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