An efficient co-swarm particle swarm optimization for non-linear constrained optimization |
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| Affiliation: | 1. Department of Civil Engineering, University of Birjand, Birjand, Iran;2. Young Researchers and Elite Club, Kerman Branch, Islamic Azad University, Kerman, Iran;1. College of Information Science and Technology, University of Nebraska at Omaha, USA;2. Chinese Academy of Sciences, Beijing, China;1. Department of Civil Engineering, University of Birjand, Birjand, Iran;2. Department of Civil Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran |
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| Abstract: | This paper proposes a new co-swarm PSO (CSHPSO) for constrained optimization problems, which is obtained by hybridizing the recently proposed shrinking hypersphere PSO (SHPSO) with the differential evolution (DE) approach. The total swarm is subdivided into two sub swarms in such a way that the first sub swarms uses SHPSO and second sub swarms uses DE. Experiments are performed on a state-of-the-art problems proposed in IEEE CEC 2006. The results of the CSHPSO is compared with SHPSO and DE in a variety of fashions. A statistical approach is applied to provide the significance of the numerical experiments. In order to further test the efficacy of the proposed CSHPSO, an economic dispatch (ED) problem with valve points effects for 40 generating units is solved. The results of the problem using CSHPSO is compared with SHPSO, DE and the existing solutions in the literature. It is concluded that CSHPSO is able to give the minimal cost for the ED problem in comparison with the other algorithms considered. Hence, CSHPSO is a promising new co-swarm PSO which can be used to solve any real constrained optimization problem. |
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| Keywords: | Particle swarm optimization Differential evolution Economic dispatch problem Mutation |
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