An Improved Ant Colony Optimization Algorithm for Vehicle Routing Problem with Time Windows

Abstract

Distribution plays an essential role in the supply chain system. One of the most challenging problems in distribution is determining vehicle routes. The purpose of this research is to propose the Improved Ant Colony Optimization (IACO) Algorithm for solving the Vehicle Routing Problem with Time Windows (VRPTW) to minimize distance while taking into account the destination customer's vehicle capacity and time windows. The proposed IACO algorithm is based on the conventional ACO algorithm but with the addition of local search and mutation processes. Numerical experiments were performed to ensure that the resulting route did not violate the VRPTW constraint. Furthermore, this study compares the performance of IACO with other metaheuristic algorithms. It analyzes the effect of iteration on distance, the number of routes, and computation time. The numerical experiments show that the proposed IACO algorithm can minimize the distance.

An integrated Optimization Model of Product Mix, Assortment Packing, and Distribution in A Fashion Footwear Company

“…Several VRP variants are commonly used, including Capacitated VRP, VRP with Time Windows (VRPTW), and Multiple Depot VRP (MDVRP). In this study, due to specific capacity constraints for vehicles involved in the product distribution process, a capacitated VRP model (CVRP) is chosen, where each vehicle starts and ends its route at the distribution center (DC) [18]. e model in this study is developed based on the research of Wang et al [7], which discusses the development of an optimization model for the assortment packing process and the application of collaborative shipping on fashion products.…”