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BIBTEX RIS

Discovering Promising Regions to Help Global Numerical Optimization Algorithms

2007; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-540-76631-5_8

1611-3349

Vinícius Veloso de Melo, Alexandre C. B. Delbem, Dorival Leão Pinto Júnior, Fernando Marques Federson,

Evolutionary Algorithms and Applications

We have developed an algorithm using a Design of Experiments technique for reduction of search-space in global optimization problems. Our approach is called Domain Optimization Algorithm. This approach can efficiently eliminate search-space regions with low probability of containing a global optimum. The Domain Optimization Algorithm approach is based on eliminating non-promising search-space regions, which are identifyed using simple models (linear) fitted to the data. Then, we run a global optimization algorithm starting its population inside the promising region. The proposed approach with this heuristic criterion of population initialization has shown relevant results for tests using hard benchmark functions.