A Heuristic Enhancing Artificial Immune System for Three-dimensional Loading Capacitated Vehicle Routing Problem

Peeraya Thapatsuwan (Department of Computational Science and Digital Technology, Faculty of Liberal Arts and Science, Kasetsart University Kamphaeng Saen Campus, Thailand)
Warattapop Thapatsuwan (Department of Computational Science and Digital Technology, Faculty of Liberal Arts and Science, Kasetsart University Kamphaeng Saen Campus, Thailand)
Chaichana Kulworatit (Department of Computer Science, School of Science, King Mongkut’s Institute of Technology Ladkrabang, Thailand)

Journal of Applied Engineering and Technological Science (JAETS)
Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)

This study addresses the Three-Dimensional Loading Capacitated Vehicle Routing Problem (3L-CVRP), a highly complex NP-hard problem that combines vehicle routing with spatially constrained three-dimensional bin packing. To tackle this challenge, we propose an enhanced Artificial Immune System (En-AIS) that integrates a novel local search heuristic called “Bring-i-to-j,” designed to improve routing feasibility and loading efficiency. The En-AIS algorithm is further refined through rigorous parameter tuning using a full factorial design and ANOVA analysis. Comparative experiments were conducted against conventional AIS and the Firefly Algorithm (FA) across 27 benchmark instances. Results demonstrate that En-AIS consistently outperforms both baseline methods in terms of solution quality, achieving an average improvement of 15–20% while maintaining competitive computational times. These findings highlight the algorithm’s robustness and its practical potential for application in logistics and supply chain optimization tasks involving joint routing and loading decisions.