Title: Performance improvement of real coded genetic algorithm with Quadratic Approximation based hybridisation

Authors: Kusum Deep, Kedar Nath Das

Addresses: Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India. ' Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India

Abstract: Due to their diversity preserving mechanism, real coded genetic algorithms are extremely popular in solving complex non-linear optimisation problems. In recent literature, Deep and Thakur (2007a, 2007b) proved that the new real coded genetic algorithm (called LX-PM that uses Laplace Crossover and Power Mutation) is more efficient than the existing genetic algorithms that use combinations of Heuristic Crossover along with Non-Uniform or Makinen, Periaux and Toivanen Mutation. However, there are some instances where LX-PM needs improvement. Hence, in this paper, an attempt is made to improve the efficiency and reliability of this existing LX-PM by hybridising it with quadratic approximation (called H-LX-PM). To realise the improvement, a set of 22 benchmark test problems and two real world problems, namely: a) system of linear equations; b) frequency modulation parameter identification problem, have been considered. The numerical and graphical results confirm that H-LX-PM really exhibits improvement over LX-PM in terms of efficiency, reliability and stability.

Keywords: hybrid genetic algorithms; real coded genetic algorithms; Laplace crossover; power mutation; quadratic approximation; efficiency; reliability; stability.

DOI: 10.1504/IJIDSS.2009.031415

International Journal of Intelligent Defence Support Systems, 2009 Vol.2 No.4, pp.319 - 334

Published online: 02 Feb 2010 *

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