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发生自然灾害或人为的社会动荡事件以后,决策者希望在较短的时间内找出一条最优的应急物资配送路径,第一时间将应急物资配送到受灾地区。但是对于路径的走行时间、运输风险等权值,往往却很难给出确定的变量,因为这些变量往往在一个范围内波动。针对上述问题,我们研究了模糊环境下应急物资配送路径优化问题。首先简单介绍了模糊理论知识,并建立了模糊环境下应急物资配送的机会约束规划模型;然后结合模糊模拟技术和遗传算法,设计了解决该模型的混合智能算法;最后引入一个实例,验证了模型与算法的有效性和可行性。
In the wake of natural disasters or man-made social unrest, policymakers hope to find an optimal distribution route for emergency supplies in a relatively short period of time, and deliver the emergency supplies to affected areas as soon as possible. However, it is often difficult to give a definite variable for the travel time of the route, the weight of the transport risk, etc., because these variables tend to fluctuate within a certain range. In view of the above problems, we study the optimization of emergency material delivery route in fuzzy environment. First of all, the knowledge of fuzzy theory is briefly introduced and a chance constrained programming model of emergency materials distribution in fuzzy environment is established. Then, a hybrid intelligent algorithm to solve this problem is designed with fuzzy simulation and genetic algorithm. Finally, an example is given to verify the model With the validity and feasibility of the algorithm.