Reeves, Colin R. [Ahnja, Ravindra K.; Orlin, James B.; Kershenbaum, Aaron; Levine, David; Ross, Peter] Genetic algorithms for the operations researcher. (English) Zbl 0893.90145 INFORMS J. Comput. 9, No. 3, 231-250, commentaries 251-265 (1997). Summary: Genetic algorithms have become increasingly popular as a means of solving hard combinatorial optimization problems of the type familiar in operations research. This feature article will consider what genetic algorithms have achieved in this area, discuss some of the factors that influence their success or failure, and offer a guide for operations researchers who want to get the best out of them. Cited in 39 Documents MSC: 90C27 Combinatorial optimization 68T05 Learning and adaptive systems in artificial intelligence 90-02 Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming 90C35 Programming involving graphs or networks 90C10 Integer programming Keywords:genetic algorithms Software:OR-Library PDFBibTeX XMLCite \textit{C. R. Reeves}, INFORMS J. Comput. 9, No. 3, 231--250, commentaries 251--265 (1997; Zbl 0893.90145) Full Text: DOI