Self Adaptive Hybridization of Quadratic Approximation with Real Coded Genetic Algorithm
The real coded Genetic Algorithm (LX-PM) that uses Laplace Crossover and Power mutation became popular to find optimal solution. In recent past, the LX-PM is being hybridized with a local search called Quadratic Approximation (QA) to improve the solution quality. However, there are some instances to improve it further, just by checking the frequency of hybridization. In this paper, a self adaptive strategy of hybridization is incorporated in the cycle of LX-PM. The improved efficiency and efficacy of the adaptive hybridization of QA over the simple hybridization of QA with LX-PM, is being realized through a set of 22 unconstrained benchmark problems. Comparative result is being analyzed through the numerical results, in terms of five different aspects.
KeywordsHybrid real coded genetic algorithm Laplace crossover Power mutation and quadratic approximation
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