Emergency resources scheduling based on adaptively mutate genetic algorithm

Authors:
Liming Zhang;Yuhua Lin;Guofeng Yang;Huiyou Chang
Affiliations:
Department of Computer Science, Sun Yat-sen University, Guangzhou 510275, China;Department of Computer Science, Sun Yat-sen University, Guangzhou 510275, China;School of Software, Sun Yat-sen University, Guangzhou 510275, China;School of Software, Sun Yat-sen University, Guangzhou 510275, China
Venue:
Computers in Human Behavior
Year:
2011

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Abstract

The emergency resources dispatch is critical in emergency relief, while it is quite difficult to achieve an optimized scheduling, adjusting to a practical situation. In this paper, an emergency resources scheduling model is built, which simulates realistic problems, this model includes multiple suppliers with a variety of resources, a single accident site and some restrictions, all these elements closing to a practical event. Then we applied an adaptively mutate genetic algorithm to figure out a superior solution, which adopts the Binary Space Partitioning tree for heuristic searching and adaptive mutation. Finally, we compare the experimental results obtained by canonical genetic algorithm and the adaptively mutate genetic algorithm, respectively. As is observed, this novel method proposed in our work has acquired better solutions than canonical genetic algorithm.