A research survey: review of AI solution strategies of job shop scheduling problem
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering,Software
Link
http://link.springer.com/content/pdf/10.1007/s10845-013-0837-8.pdf
Reference108 articles.
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2. Asadzadeh, L., & Zamanifar, K. (2010). An agent-based parallel approach for the job shop scheduling problem with genetic algorithms. Mathematical and Computer Modelling, 52, 1957–1965.
3. Aydın, M. E., & Oztemel, E. (2000). Dynamic job-shop scheduling using reinforcement learning agents. Robotics and Autonomous Systems, 33, 169–178.
4. Aydın, E., & Fogarty, T. C. (2004). A simulated annealing algorithm for multi-agent systems: A job shop scheduling application. Journal of Intelligent Manufacturing, 15, 805–814.
5. Bierwirth, C., & Mattfeld, D. C. (1999). Production scheduling and rescheduling with genetic algorithms. Evolutionary Computation, 7(1), 1–17.
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