A Computational Time Analysis of Dhouib-Matrix-SPP versus Particle Swarm Optimization Metaheuristics for Grid-based Path Planning

DOI: https://doi.org/10.19139/soic-2310-5070-3259
Keywords: Artificial Intelligence, Particle Swarm Optimization, Mobile robot path planning, Metaheuristic, Optimization

Abstract

Actually, path planning is one of the most fundamental aspects of mobile robots study. The objective is to determine the shortest feasible trajectory from a starting point to a goal location while avoiding obstacles. Particle Swarm Optimization (PSO) has been widely applied to this problem. However, it is often complex, requiring careful parameter tuning and extensive computational resources, in spite of that it suffers from high computational complexity, sensitivity to parameter tuning, and local optima stagnation. To overcome these limitations, the new Dhouib-Matrix-SPP (DM-SPP) method is proposed, which is rapid, straightforward, and does not require parameter adjustment. Simulation experiments on four case studies (I-shaped, U-shaped, T-shaped and Randomly shaped) demonstrate that DM-SPP consistently outperforms the ranking Particle Swarm Optimization (rPSO) metaheuristic and the artificial potential field-based Particle Swarm Optimization (apfrPSO) metaheuristic in terms of computational time: DM-SPP is 66 time rapider than the rPSO metaheuristic and 31 time rapider than the apfrPSO metaheuristic. These findings indicate that DM-SPP is a powerful and scalable approach for mobile robot path planning.

Author Biography

Souhail Dhouib, Higher Institute of Industrial Management, University of Sfax, TUNISIA
- Listed as one of the World’s Top 2% Scientists in the main field “Information & Communication Technologies”, the first subfield of “Artificial Intelligence” and the second subfield of “Operations Research” (by Stanford University and Elsevier),- Ranked 29th world’s best researcher in the discipline of Metaheuristic by ScholarGPS (prior to five years),- Ranked 71th world’s best researcher in the discipline of Industrial Engineering and Operations Research by ScholarGPS (prior to five years),- Ranked 106th world’s best researcher in the discipline of Mobile Robot by ScholarGPS (prior to five years),- Inventor of a new Artificial Intelligence optimization concept, namely the "Dhouib-Matrix",- Taking part in the Frontiers Planet Prize and the African Planet Prize as contact point, coordinator and nominator,- Expert evaluator for the International Science Foundation,- Keynote speaker and workshop holder for several international conferences.
Published
2026-01-04
How to Cite
Dhouib, S., Kallel, D., Beji, N., & Dhouib, S. (2026). A Computational Time Analysis of Dhouib-Matrix-SPP versus Particle Swarm Optimization Metaheuristics for Grid-based Path Planning. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-3259
Issue
Online First
Section
Research Articles
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