Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Global Optimization
Evolutionary algorithms for the satisfiability problem
Evolutionary Computation
Soft Genetic Operators in Evolutionary Algorithms
Evolution and Biocomputation, Computational Models of Evolution
The role of mutation and recombination in evolutionary algorithms
The role of mutation and recombination in evolutionary algorithms
Combinatorial optimization with use of guided evolutionary simulated annealing
IEEE Transactions on Neural Networks
Combination of Global and Local Search for Real Function Optimization
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
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This article introduces a new global optimization procedure called LARES. LARES is based on the concept of an artificial chemical process (ACP), a new paradigm which is described in this article. The algorithm's performance was studied using a test bed with a wide spectrum of problems including random multi-modal random problem generators, random LSAT problem generators with various degrees of epistasis, and a test bed of real-valued functions with different degrees of multi-modality, discontinuity and flatness. In all cases studied, LARES performed very well in terms of robustness and efficiency.