Multi-objective Flexible Job Shop Scheduling Problem Based on Monte-Carlo Tree Search

Wu, Tung-Ying; Wu, I‐Chen; Liang, Chao-Chin

doi:10.1109/taai.2013.27

Cited by 10 publications

(10 citation statements)

References 7 publications

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“…Especially hybrid MO-MCTS approaches have demonstrated their abilities by solving the Pareto Kacem benchmark problem [19,22,23]. However, the Kacem benchmark problem does not cover important restrictions (transport, setup) and does not offer process flexibility.…”

Section: Literature Reviewmentioning

confidence: 99%

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Hybrid Monte Carlo tree search based multi-objective scheduling

Hofmann

Liu

May

et al. 2022

Prod. Eng. Res. Devel.

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As markets demand targeted products for highly differentiated use cases, the number of variants in production increases, whilst the volume per variant decreases. Different product variants result in differences in work content on workstation level which cause takt time losses and result in a poor utilization. In this context, matrix-structured production systems with neither temporal nor spacial linkage emerged to reduce the effects of different work content on the entire production system. However, matrix-structured production systems require far more complex production control. To that end, this paper presents a scheduling approach. The proposed scheduling system considers variable process sequences and their allocation to different workstations in order to optimize scheduling objectives. This contribution presents a Monte Carlo tree search based optimizer combined with local search as post optimizer to derive schedules in a short time span to enabling reactive scheduling. The application of the scheduler to a benchmark problem and an industrial scheduling problem demonstrates the quality of the results and illustrates how the scheduler reassigns the work content dynamically.

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Section: Literature Reviewmentioning

confidence: 99%

“…Local search by moving one operation (LSONE) [27] combined with MO-MCTS [22] has achieved remarkable performance on the Kacem benchmark problems. However, LSONE does not consider transport and setup times since the original Kacem problem is only a simplified form of a matrix production.…”

Section: Local Search Post Optimizermentioning

confidence: 99%

Hybrid Monte Carlo tree search based multi-objective scheduling

Hofmann

Liu

May

et al. 2022

Prod. Eng. Res. Devel.

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“…The exploitation means that the MCTS takes an advantage of the best option we know. The algorithm repeats the following four phases [16]: (1. ) Selection: The algorithm starts from the root node and recursively chooses the best child based on the UCB formula until a leaf node is reached.…”

Section: Monte Carlo Tree Searchmentioning

confidence: 99%

Parallel Machine Scheduling With Monte Carlo Tree Search

Agárdi

Nehéz

2021

Acta Polytech

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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 datasets.

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“…In addition, the literature shows that they can be successfully used for various scheduling problems (Shaw, ; Gu et al., ; Wang et al., ; Babayan and He, ). These problems serve as a reference for other problem resolution techniques in the field of resource assignment, for example, the vehicle routing problem and the resource assignment problem in classrooms (Liu et al., ; Wu et al., ; Rahimi et al., ; Zheng et al., ). Traditional approaches for resolution of the FJSSP are as varied as the different formulations of the problem.…”

Section: Introductionmentioning

confidence: 99%

“…Traditional approaches for resolution of the FJSSP are as varied as the different formulations of the problem. They include fast, simple heuristics, taboo search (Liouane et al., ), evolutionary approaches (Gu et al., ; Zhang et al., ; Ma et al., a; Ma et al., b; Yuan and Xu, ; Zheng et al., ), Monte‐Carlo Tree Search (Wu et al., ), simulated annealing (SA) (Shivasankaran et al., ), and modern hybrid metaheuristics that consolidate the advantages of different approaches (Zhou et al., ). The FJSSP is an extension of classic JSSP, and incorporates all the difficulties and complexities of this problem (Mastrolilli and Gambardella, ; Kacem et al., , ; Ho and Tay, ; Chen and Chen, ; Amiri et al., ; Mati et al., ; Knopp et al., ).…”

Section: Introductionmentioning

confidence: 99%

Accelerated simulated annealing algorithm applied to the flexible job shop scheduling problem

Cruz-Chávez

Martínez-Rangel

Cruz-Rosales

2015

Int Trans Operational Res

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This paper presents a simulated annealing algorithm accelerated by a partial scheduling mechanism and a cooling schedule mechanism that is a function of the standard deviation. This facilitates a rapid approach to good solutions in the flexible job shop scheduling problem (FJSSP). The results demonstrate that for benchmark instances of several sizes, simulated annealing that implements the proposed mechanism converges more quickly to good solutions than simulated annealing that does not implement the proposed mechanism.

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Multi-objective Flexible Job Shop Scheduling Problem Based on Monte-Carlo Tree Search

Cited by 10 publications

References 7 publications

Hybrid Monte Carlo tree search based multi-objective scheduling

Hybrid Monte Carlo tree search based multi-objective scheduling

Parallel Machine Scheduling With Monte Carlo Tree Search

Accelerated simulated annealing algorithm applied to the flexible job shop scheduling problem

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