Static-Dynamic route optimization using genetic algorithm

Jocelyn L. Garrido; Paul Joseph M. Estrera; Ma. Esther B.Chio; Rhea Suzette M. Haguisan

Author(s)

Jocelyn L. Garrido Department of Information Technology, University of Science and Technology of Southern Philippines, Cagayan de Oro City, Philippines

Paul Joseph M. Estrera Department of Information Technology, University of Science and Technology of Southern Philippines, Cagayan de Oro City, Philippines

Ma. Esther B.Chio Department of Information Technology, University of Science and Technology of Southern Philippines, Cagayan de Oro City, Philippines

Rhea Suzette M. Haguisan Department of Information Technology, University of Science and Technology of Southern Philippines, Cagayan de Oro City, Philippines

Abstract

Route optimization is prevalent in providing cost-effective, time-saving, and fuel-efficient logistic operations. In the case of a laundry shop using a Laundry Management System (LMS) which provides pickup and drop-off services to their increasing clients, the absence of route planning for drop-off and pickup led to frequent vehicle traversal increasing the operational cost of logistics. This was addressed by developing a web and mobile application that provides a static drop-off and dynamic pickup route plan using a Genetic Algorithm (GA) which was integrated into the existing LMS. Genetic Algorithm (GA) has been known as a technique useful for finding the optimal or near-optimal solutions for combinatorial optimization problems. Optimization was evident by generating a lesser number of vehicles with a shorter distance traveled for each vehicle while taking into consideration the vehicle payload. This can maximize productivity and improve work efficiency while saving operational costs. Implementation of a dynamic route plan for pickup during vehicle enroute within EDT also contributed to the efficiency to handle the increasing demand of the client. While route optimization in this study considers only distance travel, vehicle capacity, and time window, we recommend further research using artificial intelligence considering traffic situations, rerouting due to road maintenance, and other road-related situations that can affect the route plan enroute.

Publication Details

Page(s) 499-504

DOI DOI not available

Published Journal: Science International, Volume: 34, Issue: 6, Year: 2022

Request the full text from PASTIC

Keywords

Genetic Algorithm, Route Optimization, Dynamic Route Plan, Vehicle Routing Problem (VRP)