Modified Camel Algorithm for Optimizing Green Vehicle Routing Problem with Time Windows

Abstract

In recent years, the issue of fuel depletion has become a significant problem in the world. The logistics sector is one of the sectors with an increase in fuel consumption. Therefore, route optimization is one of the attempts to solve the problem of minimization fuel consumption. In addition, this problem generally also has time windows. This study aimed to solve the Green Vehicle Routing Problem with Time Windows (GVRPTW) using the Camel Algorithm (CA). The objective function in this problem was to minimize the total cost of distribution, which involves the cost of fuel consumption and the cost of late delivery. The CA parameter experiment was conducted to determine the effect of the parameter on distribution cost and the computation time. In addition, this study also compared the CA algorithm's performance with the Local search algorithm, Particle Swarm Optimization, and Ant Colony Optimization. Results of this study indicated that the use of Camel population parameters and the total journey step affected the quality of the solution. Furthermore, the research results showed that the proposed algorithm had provided a better total distribution cost than the comparison algorithm.