Research On Location Routing Problem With Simultaneous Pickup And Delivery Based On Fuzzy Time Windows

The location routing problem (LRP), which simultaneously tackles both facility locationand the vehicle routing decisions to rationally allocate resources capacity and minimize thetotal system cost, is of great importance in designing an integrated logistic distributionnetwork under the background of e-commerce and environmental logistics.In practice, customers can have pickup and delivery demands and they often request thatboth demands should be met at the same time. Besides, customers ususally have flexibleservice due-time in real-life distribution process. By taking into consideration this kind ofdemand structure of customers, in this paper, we address a variant of the LRP which. Afteranalyzing a variety of conventional constraints, we presented a bi-objective capacitatedlocation routing problem with simultaneous pickup and delivery based on fuzzy timewindows. This paper mainly analyzes and studies from the following aspects:On the basis of the theory of nonlinear mixed integer programming, the paper presenteda bi-objective capacitated location routing problem (CLRP) model with simultaneous pickupand delivery based on fuzzy time windows, which regarded taking capacity constraints ondepots and routes into consideration.To solve the complex model, a two-phase simulated annealing algorithm (SA) basedhybrid genetic algorithm (GA) was developed. In the first phase, the proposed algorithmmodified the population generation rule, genetic operators and recombination strategy andrealized the combination of the local searching ability of SA and global searching ability ofGA.In the second phase, a fuzzy optimization procedure was embedded, whice optimizes thecustomer satisfaction within the acceptable time window.Finally, based on the seven simulation examples, the validity of the model and algorithmis verified. The simulation experiment shows that the two-phrase hybrid genetic algorithm cangive satisfactory solution in a short time and the proposed model can balance the logistics costand customer service level. They can be provided to be alternative tools for real-life locationand routing decision.