Kaelo, P.; Ali, M. M. Integrated crossover rules in real coded genetic algorithms. (English) Zbl 1137.90735 Eur. J. Oper. Res. 176, No. 1, 60-76 (2007). Summary: Modifications in crossover rules and localization of searches are suggested to the real coded genetic algorithms for continuous global optimization. Central to our modifications is the integration of different crossover rules within the genetic algorithm. Numerical experiments using a set of 50 test problems indicate that the resulting algorithms are considerably better than the previous version considered and offer a reasonable alternative to many currently available global optimization algorithms, especially for problems requiring ‘direct search type’ methods. Cited in 8 Documents MSC: 90C59 Approximation methods and heuristics in mathematical programming 90C26 Nonconvex programming, global optimization Keywords:genetic algorithms; global optimization; direct search methods; probabilistic adaptation Software:Genocop PDFBibTeX XMLCite \textit{P. Kaelo} and \textit{M. M. Ali}, Eur. J. Oper. Res. 176, No. 1, 60--76 (2007; Zbl 1137.90735) Full Text: DOI References: [1] Ali, M. M.; Törn, A., Population set based global optimization algorithms: Some modifications and numerical studies, Computers and Operations Research, 31, 10, 1703-1725 (2004) · Zbl 1073.90576 [2] Ali, M. M.; Törn, A.; Viitanen, S., A numerical comparison of some modified controlled random search algorithms, Journal of Global Optimization, 11, 377-385 (1997) · Zbl 0891.90144 [3] Ali, M. M.; Khompatraporn, C.; Zabinsky, Z. 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