Biased random-key genetic algorithm for nonlinearly-constrained global optimization

• Published in: 2013 IEEE Congress on Evolutionary Computation pp. 2201 - 2206
• Main Authors: Silva, Ricardo M. A., Resende, Mauricio G. C., Pardalos, Panos M., Faco, Joao L.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2013
• Subjects: Decoding; Genetic algorithms; Linear programming; Optimization; Sociology; Statistics; Vectors

Global optimization seeks a minimum or maximum of a multimodal function over a discrete or continuous domain. In this paper, we propose a biased random key genetic algorithm for finding approximate solutions for bound-constrained continuous global optimization problems subject to nonlinear constrain...