Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Search space reduction in QoS routing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Epistasis in Genetic Algorithms: An Experimental Design Perspective
Proceedings of the 6th International Conference on Genetic Algorithms
Advances in evolutionary computing
Kriging as a surrogate fitness landscape in evolutionary optimization
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Design and Analysis of Experiments
Design and Analysis of Experiments
An orthogonal genetic algorithm for multimedia multicast routing
IEEE Transactions on Evolutionary Computation
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
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We have developed an algorithm for reduction of search-space, called Domain Optimization Algorithm (DOA), applied to global optimization. This approach can efficiently eliminate search-space regions with low probability of containing a global optimum. DOA basically worksusing simple models for search-space regions to identify and eliminate non-promising regions. The proposed approach has shown relevant results for tests using hard benchmark functions.