A Multi-objective Algorithm Based on M-MOEA/D Algorithm and Tissue-Like P System for Solving Bi-objective Grain Dispatching and Transportation

The vehicle routing problem with time windows (VRPTW) is a classic NP-Hard problem, which has theoretical research value and practical significance. Intelligent optimization algorithms can solve the problem effectively. Among them, the intelligent optimization algorithm based on the membrane computing can combine the parallel computing of the membrane with the precision and efficiency of the intelligent optimization algorithm, and it has become a research hotspot. In this paper, we propose an effective bi-objective optimization algorithm based on M-MOEA/D and tissue-like P system, named TM-MOEA/D, to solve bi-objective VRPTW. It uses the parallel ability of membrane computing to improve the ability of solving VRPTW. So that, non-dominated solutions obtained by TM-MOEA/D evenly distribute and approximate Pareto front. The experimental results show that TM-MOEA/D can obtain the best solutions on the clustered customers data sets, and perform well on the remote customers data sets.