Authors: Rajesh Kumar, Devendra Sharma, Anupam Kumar
Addresses: Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, India. ' Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, India. ' Department of Electronics and Communication Engineering, Malaviya National Institute of Technology, Jaipur, India
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.
Keywords: particle swarm optimisation; PSO; multi-agent systems; MAS; bee algorithm; agent-based systems; bio-inspired computation.
International Journal of Bio-Inspired Computation, 2009 Vol.1 No.4, pp.259 - 269
Available online: 28 Apr 2009Full-text access for editors Access for subscribers Purchase this article Comment on this article