The study of comparisons of three crossover operators in genetic algorithm for solving single machine scheduling problem

DOI

10.2991/icmse-15.2015.55How to use a DOI?

Keywords

crossover operator, single machine scheduling, genetic algorithm

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.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ouyang Quan
AU  - Hongyun Xu
PY  - 2015/12
DA  - 2015/12
TI  - The study of comparisons of three crossover operators in genetic algorithm for solving single machine scheduling problem
BT  - Proceedings of the 2015 6th International Conference on Manufacturing Science and Engineering
PB  - Atlantis Press
SP  - 293
EP  - 297
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-15.2015.55
DO  - 10.2991/icmse-15.2015.55
ID  - Quan2015/12
ER  -