摘要
为解决食品冷链配送系统优化问题,针对易腐品特性,结合配送网络时变特征进行行程时间分析,根据服务时间窗设计满意度函数,建立时变条件下的仿真模型;采用"预优化阶段+实时优化阶段"两阶段求解策略,利用分解法进行问题分解,设计最小包络聚类分析方法与混合遗传算法求解。仿真计算验证了模型和算法的有效性与研究的实用价值。
In order to solve the problem of food cold chain logistics distribution system optimization problem,for perishable goods characteristics,combined with the distribution network time-varying characteristics to analyse travel time,this paper designed satisfaction degree function according to service time windows and established the simulation model under time-dependent.It designed the two-phase solution of preoptimization phase and real-time optimization phase,by using the decomposition method,it decomposed the problem,designed the minimum envelope clustering analysis method and tabu search algorithm to solve the problem.Simulation results show the effectiveness of the model and algorithm of practical value.
出处
《计算机应用研究》
CSCD
北大核心
2013年第1期183-188,共6页
Application Research of Computers
基金
国家自然科学基金资助项目(70671108)
关键词
时变网络
冷链
时间窗
设施定位
客户满意度
混合遗传算法
time-varying network
cold chain
time window
facility location
customer satisfaction degree
hybrid genetic algorithm
