A genetic algorithm encoding for a class of cardinality constraints

A genetic algorithm encoding is proposed which is able to automatically satisfy a class of important cardinality constraints where the set of distinct values of the design variables must be a subset –of cardinality not exceeding a given value– of a larger set of available items. The solution of the practically important structural optimization problem where the set of distinct values of the design variables must be a small subset of a larger set of commercially available values is used as a test-bed. Very good results have been found in the numerical experiments performed using standard binary encoding and genetic operators. Categories and Subject Descriptors I.2.8 [Problem Solving, Control Methods, and Search]: [Heuristic methods]; J.2 [Physical Sciences and Engineering]: Engineering General Terms Algorithms Keywords cardinality constraint, genetic algorithm, structural optimization

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Helio J. C. Barbosa, Afonso C. C. Lemonge
• Keywords: Cardinality Constraint, GECCO 2005, Important Cardinality Constraints, Subset –of Cardinality