With the fastest consumer demand growth, the increasing customer's demands trend to multivarieties and small-batch and the customer requires an efficient distribution planning. How to plan the vehicle route to meet customer satisfaction of mass distribution as well as reduce the fuel consumption and emission has become a hot topic. This paper proposes a two-phase optimization method to handle the vehicle routing problem, considering the customer demands and time windows coupled with multivehicles. The first phase of the optimization method provides a fuzzy hierarchical clustering method for customer grouping. The second phase formulates the optimization en-group vehicle routing problem model and a genetic algorithm to account for vehicle routing optimization within each group so that fuel consumption and emissions are minimized. Finally, we provide some numerical examples. Results show that the two-phase optimization method and the designed algorithm are efficient.
Meng, F., Ding, Y., Li, W., & Guo, R. (2019). Customer-Oriented Vehicle Routing Problem with Environment Consideration: Two-Phase Optimization Approach and Heuristic Solution. Mathematical Problems in Engineering, 2019. https://doi.org/10.1155/2019/1073609