A discrete human behavior-based approach for vehicle routing problem of multiple cross-docking networks

Abstract

In this study, the vehicle routing problem of multiple cross-docking centers is considered to minimize total transportation distance of the vehicles. For the considered problem, the split delivery of the customer is allowed where a supplier or customer node can be serviced by more than one vehicle. By this assumption, the demand of a customer can be transported through different cross-docking centers. The aim of the problem is to find best vehicle routes that minimize total transportation distance of the fleet. The problem is formulated as a mixed integer mathematical model regarding the transportation times. To solve the problem, a human behavior-based optimization approach, which is recently introduced to solve continuous optimization problems, is taken into account and the discrete version of this algorithm is introduced by adapting a permutation based encoding and ordered crossover operator to generate new solutions. In computational studies, the performance of the proposed approach is tested on a problem set and the results are compared with the best integer solution of CPLEX obtained with a computational time limit. The results show that the proposed algorithm is capable to find effective solution for the transportation plans of multiple cross-docking centers.