Changing representations during search: A comparative study of delta coding
Evolutionary Computation
Binary Representations of Integers and the Performance of Selectorecombinative Genetic Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Properties of Gray and Binary Representations
Evolutionary Computation
On the application of linear transformations for genetic algorithms optimization
International Journal of Knowledge-based and Intelligent Engineering Systems
Quad search and hybrid genetic algorithms
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
A binary encoding supporting both mutation and recombination
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Gray, binary and real valued encodings: quad search and locality proofs
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
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Wolpert and Macready's No Free Lunch theorem proves that no search algorithm is better than any other over all possible discrete functions. The meaning of the No Free Lunch theorem has, however, been the subject of intense debate. We prove that for local neighborhood search on problems of bounded complexity, where complexity is measured In terms of number of basins of attraction in the search space a Gray coded representation is better than Binary in the sense that on average it induces fewer minima in a Hamming distance 1 search neighborhood.