A decomposition-based approach to flexible flow shop scheduling under machine breakdown

Wang, K.; Choi, Shiu Hong

doi:10.1080/00207543.2011.571456

Cited by 45 publications

(14 citation statements)

References 34 publications

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“…In a real-world distributed permutation flowshop, however, scheduling is a reactive process in which unexpected events may render the generated schedules infeasible. Since machine breakdown commonly occurs after long-time operation in the manufacturing industry (Chen, 2006;Wang and Choi, 2012), this paper considers the DPFSP under machine breakdown.…”

Section: Problem Descriptionmentioning

confidence: 99%

A fuzzy logic-based hybrid estimation of distribution algorithm for distributed permutation flowshop scheduling problems under machine breakdown

Wang

Huang

Qin

2016

Journal of the Operational Research Society

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As the research interest in distributed scheduling is growing, distributed permutation flowshop scheduling problems (DPFSPs) have recently attracted an increasing attention. This paper presents a fuzzy logic-based hybrid estimation of distribution algorithm (FL-HEDA) to address DPFSPs under machine breakdown with makespan criterion. In order to explore more promising search space, FL-HEDA hybridises the probabilistic model of estimation of distribution algorithm with crossover and mutation operators of genetic algorithm to produce new offspring. In the FL-HEDA, a novel fuzzy logic-based adaptive evolution strategy (FL-AES) is adopted to preserve the population diversity by dynamically adjusting the ratio of offspring generated by the probabilistic model. Moreover, a discrete-event simulator that models the production process under machine breakdown is applied to evaluate expected makespan of offspring individuals. The simulation results show the effectiveness of FL-HEDA in solving DPFSPs under machine breakdown.

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Section: Problem Descriptionmentioning

confidence: 99%

A fuzzy logic-based hybrid estimation of distribution algorithm for distributed permutation flowshop scheduling problems under machine breakdown

Wang

Huang

Qin

2016

Journal of the Operational Research Society

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“…Preemption is not allowed and infinite intermediate buffers exist between two successive stages. The scheduling problem is to choose a machine at each stage for each job and determine the sequence of jobs on each machine so as to minimize the makespan [14].…”

Section: Problem Statementmentioning

confidence: 99%

“…Their simulation results showed its superiority. Wang and Choi [14] proposed a decomposition-based approach that integrates the completely reactive approach with the predictive reactive approach to minimize the makespan of the flexible flowshop scheduling problem under machine breakdown. Mirabi et al [15] considered a two-stage hybrid flowshop scheduling problem where the machine may not always be available during the scheduling period.…”

Section: Introductionmentioning

confidence: 99%

A Discrete Group Search Optimizer for Hybrid Flowshop Scheduling Problem with Random Breakdown

Cui

2014

Mathematical Problems in Engineering

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The scheduling problems have been discussed in the literature extensively under the assumption that the machines are permanently available without any breakdown. However, in the real manufacturing environments, the machines could be unavailable inevitably for many reasons. In this paper, the authors introduce the hybrid flowshop scheduling problem with random breakdown (RBHFS) together with a discrete group search optimizer algorithm (DGSO). In particular, two different working cases, preempt-resume case, and preempt-repeat case are considered under random breakdown. The proposed DGSO algorithm adopts the vector representation and several discrete operators, such as insert, swap, differential evolution, destruction, and construction in the producers, scroungers, and rangers phases. In addition, an orthogonal test is applied to configure the adjustable parameters in the DGSO algorithm. The computational results in both cases indicate that the proposed algorithm significantly improves the performances compared with other high performing algorithms in the literature.

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“…By algorithm, these can be divided into classical algorithms, approximation algorithms and intelligent algorithms [1][2][3][4][5][6][7][8][9][10]. Classical algorithms include the dynamic programming method and branch and bound algorithm; the approximation algorithms include the simulation algorithm, NEH algorithm and Lagrangian relaxation algorithm; and intelligent algorithms include the annealing algorithm, tabu search algorithm and genetic algorithm [11][12][13][14][15][16][17][18]. These algorithms are very effective in solving specific problems, but all subject to some limitations.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Objective Scheduling Optimization Model Considering Product Blockage and Machine Faults

Yin¹,

Liu²,

Yeh³

2017

Int. j. simul. model.

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Considering problems like product blockage and machine faults in the batch scheduling of product assembly lines, this paper proposes a multi-objective flow shop batch scheduling model taking these problems into account, and by comparing with the traditional flow shop scheduling model, it verifies the feasibility and superiority of this model. The results show that, regarding the product blockage problem, this paper improves the MWH heuristic algorithm, leading to better quality of the initial population produced; and that it also proposes a new ISBOX crossover operator algorithm, which is used in combination with the nondominated solution information to calculate the new solution for offsprings, improving the local search capability of the algorithm. In order to address machine faults, this paper obtains new solutions by optimizing the maximum completion time and the early completion time, takes the new solutions as the initial population, and uses the proposed model to optimize the robustness and stability of the existing algorithm. By comparing the proposed model and the traditional scheduling model in terms of product blockage and machine fault, this paper finds that the proposed algorithm has high local and global convergence, and generates high-quality nondominated solutions. According to the re-scheduling strategy, this algorithm can effectively reduce the effects of product blockage and machine faults on the objective function.

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A decomposition-based approach to flexible flow shop scheduling under machine breakdown

Cited by 45 publications

References 34 publications

A fuzzy logic-based hybrid estimation of distribution algorithm for distributed permutation flowshop scheduling problems under machine breakdown

A fuzzy logic-based hybrid estimation of distribution algorithm for distributed permutation flowshop scheduling problems under machine breakdown

A Discrete Group Search Optimizer for Hybrid Flowshop Scheduling Problem with Random Breakdown

A Multi-Objective Scheduling Optimization Model Considering Product Blockage and Machine Faults

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