A Genetic Algorithm with Local Search for Solving Job Problems
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This paper presents a genetic algorithm specially designed for job shop problems. The algorithm has a simple coding scheme and new crossover and mutation operators. A simple local search scheme is incorporated in the algorithm leading to a combined genetic algorithm(CGA). It is evaluated in three famous Muth and Thompson problems (i.e. MT6×6, MT10×10, MT20×5). The simulation study shows that this algorithm possesses high efficiency and is able to find out the optimal solutions for the job shop problems.
- Coffman, E. G., et al., Computer and Job-Shop Scheduling Theory, U.S.A., John Wiley & Sons, 1976.
- French, S., Sequencing and Scheduling: An Introduction to The Mathematics of The Job-Shop, England, Ellis Horwood Ltd., 1982.
- Barker, J. R. and McMahon, G. B., ‘Scheduling the general job shop’, Management Science, 1985, 31(5), 594–598. CrossRef
- Carlier, J. and Pinson, E., ‘An algorithm for solving the job-shop problem’, Management Science, 1989, 35(2), 164–176.
- Goldberg, D. E., Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley Publishing Company, 1989.
- Starkweather, T., et al., ‘A comparison of genetic sequencing operators’, Proceedings of The Fourth International Conference on Genetic Algorithms, SAN DIEGO, 1991, pp.69–76 41.
- Bagchi, S., et al., ‘Exploring problem-specific recombination operators for job shop scheduling’, Proceedings of The Fourth International Conference on Genetic Algorithms, SAN DIEGO, 1991, pp.10–17.
- Cao, Y.J., Wu, Q.H., ‘Mechanical design optimization by mixed-variable evolutionary programming’, Proc. IEEE International Conference on Evolutionary Computation, 1997, Indianapolis, USA, pp.443–446.
- Wu, Q.H., Cao, Y.J., ‘Stochastic optimization of control parameters in genetic algorithms’, Proc. IEEE International Conference on Evolutionary Computation, 1997, Indianapolis, USA., pp77–80.
- Nakano, R. and Yamada, T., ‘Conventional genetic algorithm for job shop problems’, Proceedings of The Fourth International Conference on Genetic Algorithms, SAN DIEGO, 1991, pp.474–479.
- Federico Delia Croce, et al., ‘A genetic algorithm for the job shop problem’, Computers & Operations Research, 1995, 22(1), 15–24. CrossRef
- Shi, G., ‘A genetic algorithm applied to a classic job-shop scheduling problem’, International Journal of Systems Science, 1997, 28(1), 25–32. CrossRef
- Yamada, T. and Nakano, R., ‘A genetic algorithm with multi-step crossover for job shop scheduling problems’, First International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications: GALESIA, 1st, Sheffield, 1995, pp.146–151.
- Muth, J. F. and Thompson, G. L., Industrial scheduling, Prentice-Hall, Englewood Cliffs, New Jersey, 1963.
- A Genetic Algorithm with Local Search for Solving Job Problems
- Book Title
- Real-World Applications of Evolutionary Computing
- Book Subtitle
- EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight Edinburgh, Scotland, UK, April 17, 2000 Proceedings
- pp 107-116
- Print ISBN
- Online ISBN
- Series Title
- Lecture Notes in Computer Science
- Series Volume
- Series ISSN
- Springer Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
- Additional Links
- Combined genetic algorithm
- local search
- job shop scheduling
- Industry Sectors
- eBook Packages
- Stefano Cagnoni (4)
- Editor Affiliations
- 4. Department of Computer Engineering, University of Parma
- Author Affiliations
- 5. Department of Electronic Engineering, Shenzhen University, Shenzhen, P. R. China
- 6. Department of Electrical Engineering and Electronics, The University of Liverpool, Liverpool, L69 3GJ, UK
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