A semantics-based dispatching rule selection approach for job shop scheduling
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/s10845-018-1421-z.pdf
Reference48 articles.
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3. Azadeh, A., Negahban, A., & Moghaddam, M. (2012). A hybrid computer simulation-artificial neural network algorithm for optimisation of dispatching rule selection in stochastic job shop scheduling problems. International Journal of Production Research, 50(2), 551–566.
4. Baykasoglu, A., Göçken, M., & Özbakir, L. (2010). Genetic programming based data mining approach to dispatching rule selection in a simulated job shop. Simulation, 86(12), 715–728.
5. Blackstone, J. H., Phillips, D. T., & Hogg, G. L. (1982). A state-of-the-art survey of dispatching rules for manufacturing job shop operations. International Journal of Production Research, 20(1), 27–45.
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