Geodesic
An Adaptive ES With a Ranking Based Constraint Handling Strategy
Yugoslav journal of operations research, Tome 24 (2014) no. 3, p. 307 .

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To solve a constrained optimization problem, equality constraints can be used to eliminate a problem variable. If it is not feasible, the relations imposed implicitly by the constraints can still be exploited. Most conventional constraint handling methods in Evolutionary Algorithms (EAs) do not consider the correlations between problem variables imposed by the constraints. This paper relies on the idea that a proper search operator, which captures mentioned implicit correlations, can improve performance of evolutionary constrained optimization algorithms. To realize this, an Evolution Strategy (ES) along with a simplified Covariance Matrix Adaptation (CMA) based mutation operator is used with a ranking based constraint-handling method. The proposed algorithm is tested on 13 benchmark problems as well as on a real life design problem. The outperformance of the algorithm is significant when compared with conventional ES-based methods.
Classification : 65K10, 90C30, 90C59
Keywords: Constrained Optimization, Evolution Strategies, Covariance Matrix Adaptation. 
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     author = {Ali Osman Kusakci and Mehmet Can},
     title = {An {Adaptive} {ES} {With} a {Ranking} {Based} {Constraint} {Handling} {Strategy}},
     journal = {Yugoslav journal of operations research},
     pages = {307 },
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     number = {3},
     year = {2014},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/YJOR_2014_24_3_a0/}
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Ali Osman Kusakci; Mehmet Can. An Adaptive ES With a Ranking Based Constraint Handling Strategy. Yugoslav journal of operations research, Tome 24 (2014) no. 3, p. 307 . http://geodesic.mathdoc.fr/item/YJOR_2014_24_3_a0/