Solving a Vehicle Routing Problem under Uncertainty by a Differential Evolution Algorithm

Abstract

Purpose: In the real world, the vehicles should return to the depot after serving the last customer's location because of decreased related costs. This paper investigates the problem of increasing service time by using the stochastic time for each tour such that the total travelling time of the vehicles is limited to a specific limit based on a defined probability. Methodology: It is proven that classic models in vehicle routing problems (VRPs) belong to the class of NP-hard ones; thus, due to its complexity using exact methods in large-scale problems, a meta-heuristic-based differential evolution (DE) algorithm is proposed. Findings: The obtained results indicate the efficiency of the proposed DE algorithm. Originality/Value: The total travel time is limited to a definite probability per cent, and other constraints (e.g., capacity and time distribution restrictions) are considered. In contrast, the total cost of the transportation is minimized.

Keywords

• vehicle routing problem
• differential evolution algorithm
• uncertainty