A Capacitated Vehicle Routing Problem with Time Windows for Fleet Management Using Ant Colony Algorithm

Abstract

This study applies ant colony algorithm to solve a capacitated vehicle routing problem with time windows for fleet management. Fleet management has an important role in supply chain for enhancing the business activity. Fleet management can faces big problems without effective planning in scheduling and choosing the best routes for the delivery. The choice of the best distance path is crucial in ensuring efficient deliveries. In the raised of problem, our objective is to minimize the distance, the fuel cost and the number of vehicles be used. Since vehicle routing problem is NP-hard nature of the problem, the ant colony optimization is used to determine the optimal solution with the assist of python software. The warehouse of the manufacturing industry is at Kempas Lama, while the location of the customers that included under consideration of our study located at Terengganu, Ipoh, Semenyih, Mentakab, Kelantan, Muar, Ayer Hitam, Seremban, Kuala Selangor, Kuantan, Pulau Pinang, Segamat and Melaka. There are five planned trips for delivery with one planned trip for one day. The variable vehicle capacity, time windows and also the customers demand were considered to obtain the optimal solution. The result of the optimal shortest distance for delivery are 1210.92 km, 1776.65 km, 1428.54 km, 2204.81 km, and 707.45 km for the five trips, respectively. Analyses have been conducted to examine the effect of capacity vehicle and time windows on fleet management. This research provides substantial insights into enhancing fleet management efficiency through algorithmic optimization.