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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.