A Novel Hybrid Real-Valued Genetic Algorithm for Optimization Problems

Since genetic algorithm lacks hill-climbing capacity, it easily falls in a trap and finds a local minimum not the true solution. In this paper, a novel hybrid real- valued genetic algorithm (NHRVGA) combined with harmony search that merits of genetic algorithm and harmony search (HS) is proposed. It provides a new architecture of hybrid algorithms, which organically merges the harmony search (HS) method into real- valued genetic algorithm (RVGA). During the course of evolvement, harmony search is used to improve the search performance and this makes NHRVGA algorithm have more powerful exploitation capabilities. Simulation and comparisons based on several well- studied benchmarks demonstrate the effectiveness, efficiency and robustness of the proposed NHRVGA.

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