突发灾害下带软时间窗多车路径搜索建模

以带软时间窗的多救援车辆路径搜索问题为建模核心,首先利用近邻启发算法对混合遗传算法进行初始化,通过迭代交换产生新的子代染色体;其次由轮盘赌法选择健康的子代染色体,引入交叉算子、变异/突变算子对子代染色体进行改良,从而得到最小总成本消耗下的医疗救援车辆行驶路径,并有效缩短车辆行驶时间;最后以非常规突发灾害下的医疗救助为案例对该模型及算法的有效性和可行性进行了说明.

Modeling of Multi vehicle Route Searching with Soft Time Windows Under Sudden onset Disaster

This study focuses on the modeling of the multi-vehicle route searching with soft time windows for medical rescue. First of all, the HGA is initialized by nearest neighbor heuristic algorithm and the new chromosomes are generated through iterated swap procedure. Secondly, the roulette wheel selection is adopted to choose fitter chromosomes to undergo genetic operations and the offspring can be improved through order crossover, heuristic mutation and inversion mutation. And thereby the optimal route for medical rescue is obtained under the minimum total cost as well as the travel time of vehicles is shorted effectively. Eventually, a medical rescue example under unconventional sudden-onset disaster is provided to demonstrate the validity and feasibility of this model and algorithm.