Title: Comparison of metaheuristic approaches for parcel delivery problem

Authors: Shamine Moganathan; Siti Noor Asyikin Mohd Razali; Nabeel Naeem Hassan Almaalei; Kavikumar Jacob

Addresses: Department of Mathematics and Statistics, Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia (Pagoh Campus), 84600 Pagoh, Johor, Malaysia ' Department of Mathematics and Statistics, Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia (Pagoh Campus), 84600 Pagoh, Johor, Malaysia ' Ministry of Education, Open Educational College, Al-Muthanna Academic Center, Republic of Iraq ' Department of Mathematics and Statistics, Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia (Pagoh Campus), 84600 Pagoh, Johor, Malaysia

Abstract: Ever since the coronavirus disease-2019 (COVID-19) outbreak, people plump for e-shopping, and it causes the delivery company to receive bulks to be delivered to customers. The complication arises when the delivery man needs to transport parcels to a vast number of houses in a trip. Due to this, they seek the shortest path in the trip to minimise the delivery cost and also the time. Hence, this study aims to scrutinise the shortest path, including runtime because the delivery problem has been categorised as an NP-hard problem. Thus, we proposed two metaheuristic techniques to be compared in this study which are ant-colony optimisation (ACO) and genetic algorithm (GA). In a nutshell, the results show that the GA technique performs better than the ACO technique in terms of distance, price, and runtime for moderate data size, which is less than 50 locations, as there were some enhancements on the methods used.

Keywords: ant-colony optimisation; ACO; genetic algorithm; delivery problem; comparison; cost; runtime.

DOI: 10.1504/IJLSM.2024.138876

International Journal of Logistics Systems and Management, 2024 Vol.48 No.1, pp.67 - 91

Received: 22 Jul 2021
Accepted: 16 Oct 2021
Published online: 03 Jun 2024 *

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