Hybrid parallel chaos optimization algorithm with harmony search algorithm

• Considering the weakness in the COA, parallel chaos optimization algorithm (PCOA) is studied in this paper.
• To obtain optimum solution accurately, harmony search algorithm (HSA) is integrated with the PCOA to form a novel hybrid optimization algorithm.
• Different chaotic maps are compared and the impacts of parallel parameter on the proposed hybrid algorithm are discussed.

The application of chaotic sequences can be an interesting alternative to provide search diversity in an optimization procedure, named chaos optimization algorithm (COA). Since the chaotic motion is pseudo-randomness and chaotic sequences are sensitive to the initial conditions, the search ability of COA is usually effected by the starting values. Considering this weakness, parallel chaos optimization algorithm (PCOA) is studied in this paper. To obtain optimum solution accurately, harmony search algorithm (HSA) is integrated with PCOA to form a novel hybrid algorithm. Different chaotic maps are compared and the impacts of parallel parameter on the hybrid algorithm are discussed. Several simulation results are used to show the effective performance of the proposed hybrid algorithm.

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