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Job shop production planning under uncertainty: A Monte Carlo rollout approach

: Simroth, A.; Holfeld, D.; Brunsch, R.


Hochschule Mittweida; Rezekne Higher Education Institution, Faculty of Engineering:
Environment. Technology. Resources. Proceedings of the 10th International Scientific Practical Conference 2015. Vol.3 : June 18-20, 2015, Rezekne
Rezekne: Rezekne Higher Education Institution, Faculty of Engineering, 2015
International Scientific Practical Conference "Environment. Technology. Resources" <10, 2015, Rezekne>
Fraunhofer IVI ()

The Monte Carlo Rollout method (MCR) is a novel approach to solve combinatorial optimization problems with uncertainties approximatively. It combines ideas from Rollout algorithms for combinatorial optimization and the Monte Carlo Tree Search in game theory. In this paper the results of an investigation of applying the MCR to a Scheduling Problem are shown. The quality of the MCR method depends on the model parameters, search depth and search width, which are strong linked to process parameters. These dependencies are analyzed by different simulations. The paper also deals with the question whether the Lookahead Pathology occurs.