Solving Vehicle Routing Problem with Stochastic Demand Using Multi-objective Evolutionary Algorithm

Vehicle Routing Problem (VRP) is a famous combinatorial optimization problem and it has been extended to a multi-objective optimization perspective. This paper targets solving VRP with stochastic demand (VRPSD) under the constraints of available time window and vehicle capacity. The objective of the problem is to simultaneously minimize total travelling distance and total drivers´ remuneration. This paper proposes a decomposition-based multi-objective evolutionary algorithm to tackle VRPSD. The proposed algorithm utilizes multi-mode mutation combined with decomposition-based selection method to enhance optimization performance of the algorithm. The simulation results show that the proposed MOEA has better performance than domination-based MOEA in terms of diversity maintenance.