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Greedy-search-based multi-objective genetic algorithm for emergency logistics scheduling
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DOI：10.1016/j.eswa.2013.10.026.png)
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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.
Keyword:
Logistics
Split delivery
Emergency logistics distribution
Multi-objective optimization
Dynamic traffic assignment
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期刊
IF:
7.5
论文数:
3.0W
被引数:
10.2W
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