DE-PSO: A NEW HYBRID META-HEURISTIC FOR SOLVING GLOBAL OPTIMIZATION PROBLEMS

Millie Pant (), Radha Thangaraj () and Ajith Abraham ()
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Millie Pant: Department of Paper Technology, Indian Institute of Technology Roorkee, Saharanpur Campus-24766, India
Radha Thangaraj: Department of Paper Technology, Indian Institute of Technology Roorkee, Saharanpur Campus-24766, India
Ajith Abraham: Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, Auburn, Washington 98071-2259, USA

New Mathematics and Natural Computation (NMNC), 2011, vol. 07, issue 03, 363-381

Abstract: This paper presents a simple, hybrid two phase global optimization algorithm called DE-PSO for solving global optimization problems. DE-PSO consists of alternating phases of Differential Evolution (DE) and Particle Swarm Optimization (PSO). The algorithm is designed so as to preserve the strengths of both the algorithms. Empirical results show that the proposed DE-PSO is quite competent for solving the considered test functions as well as real life problems.

Keywords: Differential evolution; particle swarm optimization; hybrid algorithm (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S1793005711001986

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