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.