PARALLEL MACHINE SCHEDULING WITH MONTE CARLO TREE SEARCH

Authors

  • Anita Agárdi University of Miskolc, Faculty of Mechanical Engineering and Informatics, Institute of Information Science, Miskolc-Egyetemváros, 3515, Hungary
  • Károly Nehéz University of Miskolc, Faculty of Mechanical Engineering and Informatics, Institute of Information Science, Miskolc-Egyetemváros, 3515, Hungary

DOI:

https://doi.org/10.14311/AP.2021.61.0307

Keywords:

Parallel-machine scheduling, Monte Carlo Tree Search.

Abstract

In this article, a specific production scheduling problem (PSP), the Parallel Machine Scheduling Problem (PMSP) with Job and Machine Sequence Setup Times, Due Dates and Maintenance Times is presented. In this article after the introduction and literature review the mathematical model of the Parallel Machines Scheduling Problem with Job and Machine Sequence Setup Times, Due Dates and Maintenance Times is presented. After that the Monte Carlo Tree Search and Simulated Annealing are detailed. Our representation technique and its evaluation are also introduced. After that, the efficiency of the algorithms is tested with benchmark data, which result, that algorithms are suitable for solving production scheduling problems. In this article, after the literature review, a suitable mathematical model is presented. The problem is solved with a specific Monte Carlo Tree Search (MCTS) algorithm, which uses a neighbourhood search method (2-opt). In the article, we present the efficiency of our Iterative Monte Carlo Tree Search (IMCTS) algorithm on randomly generated data
sets.

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Published

2021-04-30

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Articles