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APS 9: an improved adaptive population-based simplex method for real-world engineering optimization problems
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DOI：10.1007/s10489-017-1015-z.png)
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Abstract
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The adaptive population-based simplex (APS) algorithm is a recently-proposed optimization method for solving continuous optimization problems. In this paper, a new variant of APS, referred to as APS 9, is proposed to solve engineering optimization problems. APS 9 still follows the main structure of APS where three strategies (i.e., reflection, contraction and local search) can be used to improve the population of solutions. However, the three strategies have been significantly modified and the rules for applying them have been revised. A stagnation detection mechanism and duplicates removal step have been added. The proposed method is compared with the winners of the IEEE CEC 2005 and CEC 2011 competitions on the 22 CEC 2011 problems. The results show the superiority of APS 9 compared to the other two methods. Moreover, APS 9 has been compared with two recent optimization methods on the same test bed. The limitations of the CEC 2011 competition are also discussed and new rules that are more engineering-friendly are proposed.
Keywords:
Adaptive population-based simplex
Metaheuristics
Real-world optimization
Continuous optimization
IEEE CEC 2011 competition
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