Titlebook: Constraint-Handling in Evolutionary Optimization; Efrén Mezura-Montes Book 2009 Springer-Verlag Berlin Heidelberg 2009 Computational Intel

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https://doi.org/10.1007/978-3-319-32083-0applying the modification only in the particle best population.We show through a number of experiments how, by keeping the selection pressure on a decreasing fraction of the population, COPSO can consistently solve a benchmark of constrained optimization problems.

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Continuous Constrained Optimization with Dynamic Tolerance Using the COPSO Algorithm,applying the modification only in the particle best population.We show through a number of experiments how, by keeping the selection pressure on a decreasing fraction of the population, COPSO can consistently solve a benchmark of constrained optimization problems.

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1860-949X rithms in constrained search spaces and the adaptation of novel nature-inspired algorithms for numerical optimization with constraints. .."Constraint-Handling in Evolutionary Optimization" is an important reference for researchers, practitioners and students in978-3-642-10155-7978-3-642-00619-7Series ISSN 1860-949X Series E-ISSN 1860-9503

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An Adaptive Penalty Function for Handling Constraint in Multi-objective Evolutionary Optimization, solutions. The proposed method is simple to implement and does not need any parameter tuning. The constraint handling technique is tested on several constrained multi-objective optimization problems and has shown superior results compared to some chosen state-of-the-art designs.

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Infeasibility Driven Evolutionary Algorithm for Constrained Optimization,the population allows the algorithm to approach the constraint boundary from the infeasible side of the search space in addition to its approach from the feasible side of the search space via evolution of feasible solutions. Furthermore, “good” infeasible solutions are ranked higher than the feasibl

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