Application research of improved genetic algorithm based on machine learning in production scheduling
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/content/pdf/10.1007/s00521-019-04571-5.pdf
Reference25 articles.
1. Su N, Yi M, Zhang M (2017) Genetic programming for production scheduling: a survey with a unified framework. Complex & Intelligent Systems 3(1):41–66
2. Lei X, Song S, Chen X et al (2016) Joint optimization of production scheduling and machine group preventive maintenance. Reliability Engineering & System Safety 146:68–78
3. Rodammer FA, White KP (2015) A recent survey of production scheduling. IEEE Transactions on Systems Man & Cybernetics 18(6):841–851
4. Branke J, Nguyen S, Pickardt CW et al (2016) Automated design of production scheduling heuristics: a review. IEEE Transactions on Evolutionary Computation 20(1):110–124
5. Gonzalez J, Reeves G (2017) Master production scheduling: a multiple-objective linear programming approach. International Journal of Production Research 21(4):553–562
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