Abstract
genetic algorithm is a common method for solving combinatorial optimization problems and the selection of crossover operators in genetic algorithm will directly affect the performance of the algorithm. In this paper, we compare the performance of three crossover operators, partially mapped crossover operator (PMX), order based crossover operator (OBX), and adaptation of the edge recombination crossover operator (aERX), under same genetic algorithm framework in solving the un-weighted single machine scheduling problem with sequence dependent setup times. It is concluded that the performance of PMX crossover operator is better than the other two crossover operators from the computational results.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.