摘要
为了科学合理地进行救援物资的调度,考虑在满足处置突发应急事件需求的同时,所耗物资降到最低限度,并且从总体上最大限度地降低处置突发应急事件物资运输调度的费用。在现有研究成果的基础上引入了灰色理论的知识,建立了应急开始时间最短、出救点个数最少以及需求约束偏爱度最大的多目标灰色规划模型,并通过算例用遗传算法实现该问题的求解,通过测试优选了种群数目、交叉率和变异率三种控制参数值以提高算法性能。实验所得的数据值越大,说明调度方案越好。实验结果表明,同限期最大量算法相比,在所有物资供应点提供的物资总量一定的情况下,应急地点所需的物资数量较少时,遗传算法针对该模型的求解体现更强的优化能力,其所得适应值更高,遗传算法对于求解应急物资调度灰色规划问题的适应性较强。
In order to dispatch material scientifically and logically,considered both reducing the consumption of material and the cost of material transit dispatch to the greatest extent during the course of sufficing the requirement of dealing with the emergency.This paper introduced gray theory by using the existing results,presented the gray programming model with multi-objectives including the earliest emergency start-time,the fewest relief participant areas and the highest preference degree of requirement constraints.Solved a calculation instance by genetic arithmetic(GA).Selected preferentially three control parameters by testing to improve the performance of algorithm.The bigger value of data gained by experimentation is,the better dispatch proposal is.The results of the experimentation in this paper compare with the time limit maximum algorithm,which show that genetic algorithm manifests more optimizing capability and the better fitness values by the solution of the modal and the adaptability of genetic arithmetic is better for the solution of gray programming problem about emergency material dispatch,when the numbers of the material that all the material providers supply with emergency places are same and the numbers of the material that emergency places require are less.
出处
《计算机应用研究》
CSCD
北大核心
2010年第4期1259-1262,共4页
Application Research of Computers
基金
国家科技支撑计划资助项目(2006BAJ06B08-03)
辽宁省高等学校优秀人才支持计划资助项目(2008RC42)
国家教育部人文社会科学研究一般项目(规划项目)(09YJA630102)
关键词
应急物流
物资调度
灰色规划
白化权函数
遗传算法
多目标模型
优化
组合
emergency logistics
material dispatch
gray programming
whitening weight functions
genetic algorithm
multi-objective model
optimization
combination