Greedy-search-based multi-objective genetic algorithm for emergency logistics scheduling

被引：187

作者：

Chang, Fu-Sheng ^{[1
]}

Wu, Jain-Shing ^{[1
]}

Lee, Chung-Nan ^{[1
]}

Shen, Hung-Che ^{[2
]}

机构：

[1] Natl Sun Yat Sen Univ, Dept Comp Sci & Engn, Kaohsiung 80424, Taiwan

[2] I Shou Univ, Inst Comp & Informat Engn, Kaohsiung 840, Taiwan

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2014年 / 41卷 / 06期

关键词：

Logistics; Split delivery; Emergency logistics distribution; Multi-objective optimization; Dynamic traffic assignment; DISASTER RELIEF; OPTIMIZATION; MANAGEMENT; SELECTION; MODEL;

D O I：

10.1016/j.eswa.2013.10.026

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

To enable the immediate and efficient dispatch of relief to victims of disaster, this study proposes a greedy-search-based, multi-objective, genetic algorithm capable of regulating the distribution of available resources and automatically generating a variety of feasible emergency logistics schedules for decision-makers. The proposed algorithm dynamically adjusts distribution schedules from various supply points according to the requirements at demand points in order to minimize unsatisfied demand for resources, time to delivery, and transportation costs. The proposed algorithm was applied to the case of the Chi-Chi earthquake in Taiwan to verify its performance. Simulation results demonstrate that under conditions of a limited/unlimited number of available vehicles, the proposed algorithm outperforms the MOGA and standard greedy algorithm in 'time to delivery' by an average of 63.57% and 46.15%, respectively, based on 10,000 iterations. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：2947 / 2956

页数：10

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