What is it about?
Proposes a new hybrid algorithm called MPC (Mean-PSO-CRO), which utilizes a new Mean-Search Operator. By employing this new operator, the proposed algorithm improves the search ability on areas of the solution space that the other operators of previous algorithms do not explore. Specifically, the Mean-Search Operator helps find the better solutions in comparison with other algorithms.
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Why is it important?
• A new hybrid algorithm (called MPC) is proposed for single-objective optimization problems. • A new operator is proposed to improve searching ability. • Two parameters are introduced for balancing between the global and local search abilities of the algorithm to reach globally optimal solutions, which improve the convergence speed and results. • The MPC algorithm is tested on twenty-three well-known benchmark functions. The computational results show that the proposed algorithm is highly effective, especially for high-dimensional functions.
Perspectives
The statistical tests proved that the results were statistically significant for the MPC algorithm. From the superior results of the MPC on the majority of the high-dimensional unimodal and multimodal test functions and convergence curves, it can be concluded that the proposed algorithm benefits from high exploitation ability and fast convergence. Thus, the proposed MPC algorithm can be used as an alternative for different optimizing problems.
Le Anh Duc
Hunan University
Read the Original
This page is a summary of: A new effective operator for the hybrid algorithm for solving global optimisation problems, International Journal of Systems Science, February 2018, Taylor & Francis,
DOI: 10.1080/00207721.2018.1432780.
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