Constrained Engineering DesignOptimization using Average Differential Evolution

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2018, Vol 20, Issue 6

Abstract

The use of metaheuristics has a growing interest in solving constrained optimization problems due to the computational disadvantages of numerical methods. Metaheuristics are a powerful tool in reaching the global optimum. In this work, the Average Differential Evolution (ADE) algorithm, which is one of the newly proposed metaheuristics, has been adapted to the constrained engineering design problems. The ADE algorithm is a population-based approach with a high convergence rate. It uses a mutation operator with collective diversity in the production of candidates. The results show the robustness end effectiveness of the proposed algorithm compared to state-of-the-art algorithms in literature

Authors and Affiliations

Burhanettin Durmuş

Keywords

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  • EP ID EP423565
  • DOI 10.9790/0661-2006030713.
  • Views 70
  • Downloads 0

How To Cite

Burhanettin Durmuş (2018). Constrained Engineering DesignOptimization using Average Differential Evolution. IOSR Journals (IOSR Journal of Computer Engineering), 20(6), 7-13. https://europub.co.uk/articles/-A-423565