Solving truck-cargo matching for drop-and-pull transport with genetic algorithm based on demand-capacity fitness
Mei Lin Feng, Yaorong Cheng
Abstract
This paper mainly proposes and solves a two-phase truck-cargo (T-C) matching model for truck alliance and task set in drop-and-pull (D-P) transport. Firstly, the candidate trucks were selected for each task through feature matching between the set of trucks and the set of tasks. Next, the trucks were grouped into a truck alliance; the demand-capacity fitness (DCF) between the truck alliance and task set was computed based on the demand vector of the task set and the demand vector of the truck alliance; a T-C matching model for truck alliance and task set was established to maximize the DCF. Finally, the GA was introduced to solve the proposed model on MATLAB with and without truck alliance. The solving results show that the truck alliance can effectively improve the DCF, and optimize the allocation of social resources.