基于元胞遗传算法的多目标应急资源配置

为解决不同灾情下多目标多周期灾后救援问题，减少受灾损失，对灾后应急资源配置进行研究。从物流成本和系统损失2个方面最小化救灾行动的成本和最大化有限救灾资源的分配，建立基于路况的多目标应急资源配置模型，将帕累托前沿和超体积作为元胞遗传算法的求解性能指标，开展元胞遗传算法与遗传算法对模型的求解对比实验。结果表明:元胞遗传算法能较好地求解多目标多周期应急资源配置模型，且求解性能比遗传算法更好；通过对模型的求解，可为决策者基于不同灾情下的应急决策提供参考。

Multi-objective emergency resource distribution based on cellular genetic algorithm

In order to solve the problem of multi-objective and multi-period post-disaster rescue under different disaster situation,and mitigate the disaster losses,the post-disaster emergency resource distribution was studied.A multi-objective emergency resource distribution model based on the road conditions was established to minimize the cost of disaster rescue operation and maximize the distribution of limited disaster rescue resource from two aspects of logistics cost and system losses.The solving and comparison experiments of the model with the cellular genetic algorithm and genetic algorithm were carried out by taking the Pareto front and hypervolume as the solving performance indexes of cellular genetic algorithm.The results showed that the cellular genetic algorithm could solve the multi-objective and multi-period emergency resource distribution model well,and the solving performance was better than that of genetic algorithm.Through the solving of the model,it can provide reference for the emergency decision-making of decision-makers under different disaster situation.