Opposite Based Crow Search Algorithm for Solving Optimization Problems
Öz
This article proposes an opposite based learning (OBL) enhanced crow search algorithm (CSA) version for solving optimization problems. The proposed method, named the opposite based CSA (ObCSA), starts searching with individuals with higher fitness in the initial phase of the evolutionary process. In this way, it is aimed to improve the convergence performance of the basic CSA. To validate the proposed method, a set of benchmark test suit of different of features is chosen. Its convergence characteristic and statistical results are compared with the basic CSA. The results obtained show that the proposed method improves the convergence performance of the basic CSA. And the statistical results indicate that it manages to reach the near optimal solution and increases the quality of the solution.
Anahtar Kelimeler
Crow search algorithm, opposite based learning, optimization
Kaynakça
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