Title: IB-PSO: an inversed Butterworth particle swarm optimisation algorithm for multi-agent path planning

Authors: Ferial Laassami; Mohammed El Habib Souidi; Abdeldjalil Ledmi

Addresses: ICOSI Lab, Department of Computer Science, University of Khenchela, 40004 Khenchela, Algeria ' ICOSI Lab, Department of Computer Science, University of Khenchela, 40004 Khenchela, Algeria ' ICOSI Lab, Department of Computer Science, University of Khenchela, 40004 Khenchela, Algeria

Abstract: Path planning has an immense impact on the agents' coordination. This problem becomes more challenging to solve due to the various constraints. Recently, many optimisation techniques were proposed to solve the multi-agent path planning. However, among the most reliable techniques are those based on metaheuristic principles. In this paper, we propose a novel multi-agent path planning based on an enhanced version of the particle swarm optimisation (PSO). The inertia weight is a PSO parameter allowing the control of the exploration and the exploitation of the search space. Therefore, we propose a new inertia weight calculation method known as the inversed Butterworth particle swarm optimisation (IBPSO). The main objective of this approach is to provide an adequate transition between the exploitation and the exploration of the search space. To reflect the feasibility of this extension, we compared it with different PSO versions. The showcased results prove the efficiency of the proposed approach.

Keywords: metaheuristic; multi agent systems; path planning; particle swarm optimisation; inertia weight.

DOI: 10.1504/IJSCC.2024.143853

International Journal of Systems, Control and Communications, 2024 Vol.15 No.4, pp.387 - 410

Received: 28 Aug 2024
Accepted: 13 Nov 2024
Published online: 10 Jan 2025 *

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