Three-machine flow shop scheduling with overlapping waiting time constraints

Kim, Hyun-Jung; Lee, Jun-Ho

doi:10.1016/j.cor.2018.06.009

Cited by 16 publications

(11 citation statements)

References 32 publications

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“…The sources are a first leader selection process, a tabu list, swap and forward insertion moves, and a restart mechanism. Kim and Lee [57] recommended own research which can be drawn-out by considering multiple workstations. These are recommended in sequence-dependent setup times between the jobs on the machines.…”

Section: Research Results and Recommendations On C Max For F 2/fmentioning

confidence: 99%

“…Similarly, problems such as F 2|CV aR, no − wait|C max [158] has focused on the residual work content to conditional value-at-risk (CVaR) of the problem. The problem F 3|w i1 , w i2 |C max [57] stressed on overlapping waiting time constraints. The dual-problems F 2|CD|C max , and F 2(P )|CD|C max [40] have focused on Lagrangian metaheuristic approach for the parallel-docks to cross-dock FSP.…”

Section: Critical Reviewmentioning

confidence: 99%

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Multi-objective permutation and non-permutation flow shop scheduling problems with no-wait: a systematic literature review

2021

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Flow shop scheduling is a type of scheduling where sequence follows for each job on a set of machines for processing. In practice, jobs in flow shops can arrive at irregular times, and the no-wait constraint allows the changes in the job order to flexibly manage such irregularity. The flexible flow shop scheduling problems with no-wait have mainly addressed for flow optimization on the shop floor in manufacturing, processing, and allied industries. The scope of this paper is to identify the literature available on permutation and non-permutation flow shop scheduling with no-wait constraint. This paper organizes scheduling problems based on performance measures of variability and shop environments. The extended summary of two/three-machine and m-machine problems has been compiled, including their objectives, algorithms, parametric considerations, and their findings. A systematic appearance of both conceptual and analytical results summarizes various advances of the no-wait constraint. The paper includes independently investigated problems and suggestions for future research directions.

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Section: Research Results and Recommendations On C Max For F 2/fmentioning

confidence: 99%

Section: Critical Reviewmentioning

confidence: 99%

Multi-objective permutation and non-permutation flow shop scheduling problems with no-wait: a systematic literature review

2021

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“…On the other hand, since it is very difficult to find optimal solutions for the considered problem, it is necessary to develop effective lower bounding strategies to evaluate solutions obtained by heuristic algorithms. Also, different waiting time constraints like overlapping waiting time constraints in [23] can be considered in the future research. Finally, since the problem considered in this study is a simple type of flowshop, this problem can be extended to more practical flowshops like hybrid flowshops in which there are parallel machines in each stage.…”

Section: Discussionmentioning

confidence: 99%

“…e study in [22] considers a situation where some jobs skip the first machine in a twomachine flowshop and suggests an approximation algorithm to minimize the waiting time variation of jobs. e study in [23] considers a three-machine flowshop with overlapping waiting time constraints and proposes a branch and bound algorithm to minimize makespan.…”

Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm for a Two-Machine Flowshop with a Limited Waiting Time Constraint and Sequence-Dependent Setup Times

Lee

2020

Mathematical Problems in Engineering

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This study considers a two-machine flowshop with a limited waiting time constraint between the two machines and sequence-dependent setup times on the second machine. These characteristics are motivated from semiconductor manufacturing systems. The objective of this scheduling problem is to minimize the total tardiness. In this study, a mixed-integer linear programming formulation was provided to define the problem mathematically and used to find optimal solutions using a mathematical programming solver, CPLEX. As CPLEX required a significantly long computation time because this problem is known to be NP-complete, a genetic algorithm was proposed to solve the problem within a short computation time. Computational experiments were performed to evaluate the performance of the proposed algorithm and the suggested GA outperformed the other heuristics considered in the study.

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“…In addition, there have been studies considering variant problems with waiting time limits. Kim and Lee [31] developed a branch and bound algorithm to minimize the makespan in a three-machine flow shop with overlapping waiting time constraints. Furthermore, An et al [3] suggested a branch and bound algorithm and heuristic algorithms for a two-machine flow shop with the waiting time constraints and sequence-dependent setup times to minimize the makespan, while Lee [32] provided a genetic algorithm to minimize total tardiness for the same flow shop.…”

Section: Previous Studiesmentioning

confidence: 99%

Metaheuristics for a Flow Shop Scheduling Problem with Urgent Jobs and Limited Waiting Times

2021

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This study considers a scheduling problem for a flow shop with urgent jobs and limited waiting times. The urgent jobs and limited waiting times are major considerations for scheduling in semiconductor manufacturing systems. The objective function is to minimize a weighted sum of total tardiness of urgent jobs and the makespan of normal jobs. This problem is formulated in mixed integer programming (MIP). By using a commercial optimization solver, the MIP can be used to find an optimal solution. However, because this problem is proved to be NP-hard, solving to optimality requires a significantly long computation time for a practical size problem. Therefore, this study adopts metaheuristic algorithms to obtain a good solution quickly. To complete this, two metaheuristic algorithms (an iterated greedy algorithm and a simulated annealing algorithm) are proposed, and a series of computational experiments were performed to examine the effectiveness and efficiency of the proposed algorithms.

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Three-machine flow shop scheduling with overlapping waiting time constraints

Cited by 16 publications

References 32 publications

Multi-objective permutation and non-permutation flow shop scheduling problems with no-wait: a systematic literature review

Multi-objective permutation and non-permutation flow shop scheduling problems with no-wait: a systematic literature review

A Genetic Algorithm for a Two-Machine Flowshop with a Limited Waiting Time Constraint and Sequence-Dependent Setup Times

Metaheuristics for a Flow Shop Scheduling Problem with Urgent Jobs and Limited Waiting Times

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