Neighborhood selection using the analytical network process method for the capacitated vehicle routing problems

Abstract

Highlights: Analytical Network Process (ANP) is, for the first time, applied to select the best neighborhood structure of CVRP. ANP considers tangible and intangible criteria and relationships between criteria. Computational results indicate the importance of applying ANP. ANP examines the behaviors of the test problems by considering different criteria. Goal: This scientific research article focuses on developing a performance measurement framework for selecting the neighborhood structure of the capacitated vehicle routing problem using the ANP. The study aims to analyze the studied VRP as a multi criteria decision making process to determine the most efficient neighborhood structure. Design / Methodology / Approach: The first step was using the different neighborhood operators of the vehicle routing problem which were 2-opt, swap, and insert to analyze the problem as a multi criteria decision making process to determine the most efficient neighborhood structure for the problem under study. Secondly, ANP model was developed for the regarding problem to compare these structures to find the best one for the problem. Results: The results demonstrate that 2-opt is the best alternative for the studied CVRP. The studied approach can be used for any other type of the vehicle routing problems. Limitation of the investigation: Thirty-three test problems were determined for three different neighborhood structures. All calculation results were given in detail for comparison on different test problems taken from the literature. Practical implications: The significant contribution of this study is to help logistics companies select the most appropriate neighborhood structure to be used in solving the problem to get quality results in a very short time Originality / Value: To the best of our knowledge, in the literature, there has not been any research comparing the effects of neighborhood structures on the vehicle routing problem by analyzing ANP methodology.