模糊随机需求下应急救援中心排队选址模型及算法

Queuing location model and algorithm for emergency relief centers under fuzzy random demand

为解决应急救援中心的选址问题,在假定受灾点需求为模糊随机变量的基础上,考虑运输速度随时间的演变而变化,结合排队论和选址理论,建立带有响应时间承诺的以总运输成本最小为目标的应急救援中心选址优化模型,并结合模糊随机模拟和遗传算法提出求解上述模型的混合智能算法.通过算例验证模型的实用性和算法的有效性.通过对算例进行灵敏度分析得出:所提出的算法具有很好的鲁棒性;应急救援总成本随着受灾点数量、救援中心的个数和各受灾点需求发生率的增加而上升.

In order to solve the location problem of emergency relief centers,on the basis of assumption that demands from disaster areas are fuzzy random variable,and the factor that transportation speed changes with time is considered at the same time,a model for optimizing emergency relief center location is set up by combining location theory with queue theory.The model aims to achieve minimization of total transportation cost and guarantees response time.A hybrid intelligent algorithm which combines fuzzy random simulation with genetic algorithm is introduced to solve the proposed model.A numerical example is given to demonstrate the practicability of the model and effectiveness of the algorithm.Sensitivity analysis for the numerical example shows that the proposed algorithm is robust and the total relief cost rises with the increase of the number of disaster areas and relief centers as well as demand rates from disaster areas.