Penalty Function Methods for Constrained Optimization with Genetic Algorithms
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Cites methods from "Penalty Function Methods for Constr..."
...In order to focus the search process on the feasible region, heuristic methods discriminate among feasible and non-feasible solutions via a penalty function [51] applied to Q(5) as follows:...
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Cites background from "Penalty Function Methods for Constr..."
...The detailed descriptions of all these have been presented in [2, 17, 27-37]....
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"Penalty Function Methods for Constr..." refers background in this paper
...These approaches can be grouped in four major categories [28]: Category 1: Methods based on penalty functions - Death Penalty [2] - Static Penalties [15,20] - Dynamic Penalties [16,17] - Annealing Penalties [5,24] - Adaptive Penalties [10,12,35,37] - Segregated GA [21] - Co-evolutionary Penalties [8] Category 2: Methods based on a search of feasible solutions - Repairing unfeasible individuals [27] - Superiority of feasible points [9,32] - Behavioral memory [34]...
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