Novel variable neighborhood search heuristics for truck management in distribution warehouses problem

Akram Y Sarhan; Loai Kayed B Melhim; Mahdi Jemmali; Faycel El Ayeb; Hadeel Alharbi; Ameen Banjar

doi:10.7717/peerj-cs.1582

Novel variable neighborhood search heuristics for truck management in distribution warehouses problem

PeerJ Comput Sci. 2023 Oct 4:9:e1582. doi: 10.7717/peerj-cs.1582. eCollection 2023.

Authors

Akram Y Sarhan¹, Loai Kayed B Melhim², Mahdi Jemmali^{3

4

5

6}, Faycel El Ayeb^{7

8}, Hadeel Alharbi⁹, Ameen Banjar¹⁰

Affiliations

¹ Department of Information Technology, College of Computing and Information Technology at Khulis, University of Jeddah, Jeddah, Saudi Arabia.
² Department of Health Information Management and Technology, College of Applied Medical Sciences, University of Hafr Al Batin, Hafr Al Batin, Saudi Arabia.
³ MARS Laboratory, University of Sousse, Sousse, Tunisia.
⁴ College of Computing and Informatics, University of Sharjah, Sharjah, United Arab Emirates.
⁵ Department of Computer Science and Information, College of Science at Zulfi, Majmaah University, Al-Majmaah, Saudi Arabia.
⁶ Department of Computer Science, Higher Institute of Computer Science and Mathematics, Monastir Uuniversity, Monastir, Tunisia.
⁷ Unit of Scientific Research, Applied College, Qassim University, Saudi Arabia.
⁸ GRIFT Research Group, CRISTAL Laboratory, National School of Computer Sciences, La Manouba University, Manouba, Tunisia.
⁹ Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha'il, Hail, Saudi Arabia.
¹⁰ Department of Information Systems and Technology, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia.

Abstract

Logistics and sourcing management are core in any supply chain operation and are among the critical challenges facing any economy. The specialists classify transport operations and warehouse management as two of the biggest and costliest challenges in logistics and supply chain operations. Therefore, an effective warehouse management system is a legend to the success of timely delivery of products and the reduction of operational costs. The proposed scheme aims to discuss truck unloading operations problems. It focuses on cases where the number of warehouses is limited, and the number of trucks and the truck unloading time need to be manageable or unknown. The contribution of this article is to present a solution that: (i) enhances the efficiency of the supply chain process by reducing the overall time for the truck unloading problem; (ii) presents an intelligent metaheuristic warehouse management solution that uses dispatching rules, randomization, permutation, and iteration methods; (iii) proposes four heuristics to deal with the proposed problem; and (iv) measures the performance of the proposed solution using two uniform distribution classes with 480 trucks' unloading times instances. Our result shows that the best algorithm is $\tilde{O I S}$ , as it has a percentage of 78.7% of the used cases, an average gap of 0.001, and an average running time of 0.0053 s.

Keywords: Algorithms; Distribution warehouses; Heuristics; Truck management; Variable neighborhood search.

Grants and funding

This work was funded by the deputyship for Research & Innovation, Ministry of Education in Saudi Arabia through the project number (MoE-IF-UJ-22-4100335-2). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.