Decision support for cooperative carriers based on clustering requests and discrete particle swarm optimization

Abstract

Transportation costs constitute an important part in delivering goods to customers and have a significant influence on competitive advantage of a company. How to reduce transportation costs. Vehicle routing is a critical factor in reducing transportation costs. An effective scheme to manage fleets and determine vehicle routes for delivering goods is important for carriers to survive. In the existing literature, a variety of capacitated vehicle routing problems (VRP) have been studied. Although VRP has been extensively studied, most research results focus on one single carrier. How to achieve lower transportation costs through cooperation of carriers while fulfilling the customers' requests is an important issue. This paper aims to propose a framework to support cooperation of carriers based on a clustering algorithm and discrete particle swarm optimization (DPSO) method. To address this issue, we propose two decision models for two carriers. In the first decision model, each carrier makes decisions independently by applying the DPSO method. In the second decision model, two carriers cooperate by applying a clustering algorithm first to divide all the requests into two clusters, one cluster for each carrier, and then apply the DPSO method to each carrier to determine the routes for the corresponding cluster of requests. We have developed a simulation environment to conduct experiments to compare the performance for these two decision models. The simulation results indicate that the cooperative decision outperforms that of the independent decision model.