Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Global Optimization
Experimental analysis of binary differential evolution in dynamic environments
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
A binary-real-coded differential evolution for unit commitment problem: a preliminary study
MIWAI'11 Proceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence
A real-integer-discrete-coded differential evolution
Applied Soft Computing
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The successful application of differential evolution (DE) algorithms to various real-valued problems encourages to develop some integer-coded versions of DE for working directly with integer and discrete variables of a problem. However, in most of those works, actually a real-valued solution is just converted into a desired integer-valued solution by applying some decoding mechanisms. Only a limited number of works are found, in which attempts are made for developing an actual integer-coded DE. In this article, a novel version of DE is proposed which can work directly with real, integer and discrete variables of a problem without any conversion. Applying to two non-linear real-integer-discrete-valued engineering design problems, the proposed DE is found successful in obtaining the known best solutions of the problems.