A new hybrid multi-agent-based particle swarm optimisation technique. (29th April 2009)

• Record Type: Journal Article
• Authors: Kumar, Rajesh; Sharma, Devendra; Kumar, Anupam
• Is Part Of: International journal of bio-inspired computation. Volume 1:Number 4(2009)
• Page Start: 259
• Page End: 269
• Publication Date: 2009-04-29
• Subjects: particle swarm optimisation -- PSO -- multi-agent systems -- MAS -- bee algorithm -- agent-based systems -- bio-inspired computation; Biologically-inspired computing -- Periodicals; Computational biology -- Periodicals; 572.0285
• Languages: English
• ISSNs: 1758-0366

Abstract

This paper presents a multi-agent-based hybrid particle swarm optimisation technique. The algorithm integrates the deterministic, the multi-agent system (MAS) and the particle swarm optimisation (PSO) algorithm. An agent in hybrid multi-agent PSO (HMAPSO) represents a particle to PSO and a candidate solution to optimisation problem. All agents search parallel in an equally distributed lattice-like structure to save energy and computational time. The best solution is obtained through bee decision making process. Thus making use of deterministic search, multi-agent and bee PSO, the HMAPSO realises the purpose of optimisation. The proposed algorithm has been tested on various optimisation problems. The experimental results obtained show the robustness and accuracy of proposed HMAPSO. It also has been concluded that the proposed HMAPSO is able to generate a unique and optimal solution than the earlier reported approaches and hence can be a better option for real-time online optimisation problems.