Multi-objective fuzzy optimisation method for emergency evacuation based on hybrid intelligence algorithm under fuzzy environment
Multi-objective fuzzy optimisation method for emergency evacuation based on hybrid intelligence algorithm under fuzzy environment
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DOI：
10.1504/ijcat.2013.052799
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发表时间：
2013-03
期刊：
影响因子：
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通讯作者：
Changxi Ma;Yinzhen Li;Ruichun He;Fang Wu;Li Sun;Bo Qi
中科院分区：
文献类型：
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作者：
Changxi Ma;Yinzhen Li;Ruichun He;Fang Wu;Li Sun;Bo Qi
突发公共事件发生后，如何优化应急疏散路径，提高应急系统的响应能力，是应急管理机构面临的重要课题。在模糊环境下，选择最优疏散路线，确保伤员安全、快速地到达目的地。分别建立了应急疏散路径的机会约束规划模型和机会依赖约束规划模型，并设计了求解模型的混合智能算法。该算法将模拟技术与遗传算法相结合，按照基于优先级的编码方式产生染色体，利用模拟技术计算染色体的目标值，采用改进的轮盘赌法选择染色体产生新的群体，采用部分匹配交叉法进行交叉，采用互惠交换变异法进行变异。最后通过算例验证了该模型和算法的可行性。研究结果可以帮助应急决策者在突发公共事件发生后寻找最优路径，减少交通延误造成的人员伤亡。
After a sudden public event, how to optimise emergency evacuation routings and enhance the response capability of emergency system is an important issue for emergency management agency. In this paper, we choose the optimal evacuation routing under fuzzy environment to make sure the injured reach the destination safely and quickly. Chance-constrained programming model of emergency evacuation routings and chance-dependent constraint programming models are setup respectively and a hybrid intelligence algorithm is designed to solve the model. The algorithm, which combines simulation technique and the genetic algorithm, produces chromosomes according to priority-based coding mode, uses simulation technique to calculate target values of chromosomes, produces a new group by using improved roulette wheel method to select chromosomes, crosses by adopting the partially matched crossover method, and uses reciprocal exchange mutation method to mutate. Finally, an example is presented to validate the feasibility of this model and the algorithm. The research result can help emergency decision-makers to find an optimal route after a sudden public event and reduce the casualties caused by transportation delays.