Title: Comparative study of VNS and hybridised PSO for resource allocation in V2X communications

Authors: Ibtissem Brahmi; Souhir Elleuch; Emna Hajlaoui; Monia Hamdi; Faouzi Zarai

Addresses: NTS'COM Research Unit, ENET'COM, University of Sfax, Sfax, 3018, Tunisia; ISSAT Kasserine, University of Kairouan, Kairouan, Tunisia ' Department of MIS, College of Business and Economics, Qassim University, P.O. Box 6640, Buraidah, 51452, Saudi Arabia ' Faculty of Science and Technology of Sidi Bouzid, University of Kairouan, Sidi bouzid, 3100, Tunisia ' Research Team in Intelligent Machines, National School of Engineers of Gabes, University of Gabes, B. P. W 6072, Gabes, Tunisia ' NTS'COM Research Unit, ENET'COM, University of Sfax, Sfax, 3018, Tunisia

Abstract: Exploration into cooperative intelligent traffic systems has yielded improvements in ground transportation's efficiency, safety, and comfort. This work focuses on the resource allocation challenge within Vehicle-to-Everything (V2X) communications. To address this problem, we suggested and compared the performance of two distinct meta-heuristic algorithms. The first technique, variable neighborhood search (VNS), belongs to the category of solution-based meta-heuristics. The second technique hybridises particle swarm optimisation (PSO), a population-based meta-heuristic, with a proposed local search approach, trying to leverage the strengths and mitigate the weaknesses of both algorithms. The two proposed methods seek to optimise the system's overall throughput while ensuring minimal latency and reliability for both cellular user equipment (CUEs) and vehicle user equipment (VUEs). The algorithms proposed in this paper improve the system throughput and demonstrate its feasibility and utility for V2X communications.

Keywords: resource allocation; meta-heuristic algorithms; VNS; variable neighborhood search; PSO; particle swarm optimisation.

DOI: 10.1504/IJCNDS.2026.153759

International Journal of Communication Networks and Distributed Systems, 2026 Vol.32 No.3, pp.257 - 285

Received: 03 Apr 2024
Accepted: 05 Jul 2024
Published online: 26 May 2026 *

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