Minimizing the makespan in a flow shop environment under minimum and maximum time-lag constraints

Samarghandi, Hamed

doi:10.1016/j.cie.2019.07.048

Cited by 16 publications

(5 citation statements)

References 43 publications

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“…(2018), Li et al. (2018), Samarghandi (2019a), Goyal and Kaur (2020), Panwalkar and Koulamas (2020). Li et al.…”

Section: An Overview Of Shop Scheduling Problems Characteristicsmentioning

confidence: 99%

“…Usually, all queues are assumed to operate under the first in, first out (FIFO) discipline. This is referred as the permutation flow shop and the β field includes the entry prmu: Tsai et al (2014), Pugazhenthi and Anthony Xavior (2014), Rahmani and Heydari (2014), , Vallada et al (2015), , Yang et al (2016), Yu and Seif (2016), Laribi et al (2016), Marichelvam et al (2017), Engin and Güçlü (2018), Rossit et al (2018), , Samarghandi (2019a), Goyal and Kaur (2020), Panwalkar and Koulamas (2020). Li et al (2006), and Mastrolilli and Svensson (2011) considered the generalized flow shop variant, in which the jobs do not have to be processed in all machines.…”

Section: An Overview Of Shop Scheduling Problems Characteristicsmentioning

confidence: 99%

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Shop scheduling in manufacturing environments: a review

Márquez

Ribeiro

2022

Int Trans Operational Res

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We review the literature about shop scheduling problems in manufacturing systems, revealing the concepts and methodologies that most impact the usage of scheduling theory in manufacturing environments. We focus our attention on the job shop and flow shop problems and their variants. We emphasize the interactions between the scheduling functions and manufacturing paradigms such as Industry 4.0, Computer Integrated Manufacturing, Computer‐Aided Process Planning, Advanced Planning and Scheduling, and Integrated Process Planning and Scheduling. We describe the main components and characteristics of the scheduling ecosystem, and we discuss how the scheduling interacts with the components that make it up and how it is affected by them. The metadata collected from the digital libraries on which the review was based (ScienceDirect, Scopus, and Elsevier) made it possible to characterize the historical evolution of the main concepts of the scheduling ecosystem in terms of scientific publications and research trends in the period 2000–2020.

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“…(2018), Li et al. (2018), Samarghandi (2019a), Goyal and Kaur (2020), Panwalkar and Koulamas (2020). Li et al.…”

Section: An Overview Of Shop Scheduling Problems Characteristicsmentioning

confidence: 99%

Section: An Overview Of Shop Scheduling Problems Characteristicsmentioning

confidence: 99%

Shop scheduling in manufacturing environments: a review

Márquez

Ribeiro

2022

Int Trans Operational Res

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“…Over the 2010s, some papers have put forward the utilization of Constraint Programming (CP) as a means to tackle flowshop problem. In [11][12][13] a constraint programming approaches are proposed and compared to MILP formulations in terms of effeciency. According to [6], to this day, no comparison has yet been made between CP modelling and the B&B algorithm, and the techniques have not been applied together.…”

Section: Literature Reviewmentioning

confidence: 99%

Makespan Minimization for the Two-Stage Hybrid Flow Shop Problem with Dedicated Machines: A Comprehensive Study of Exact and Heuristic Approaches

2023

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This paper presents a comprehensive approach for minimizing makespan in the challenging two-stage hybrid flowshop with dedicated machines, a problem known to be strongly NP-hard. This study proposed a constraint programming approach, a novel heuristic based on a priority rule, and Tabu search procedures to tackle this optimization problem. The constraint programming model, implemented using a commercial solver, serves as the exact resolution method, while the heuristic and Tabu search explore approximate solutions simultaneously. The motivation behind this research is the need to address the complexities of scheduling problems in the context of two-stage hybrid flowshop with dedicated machines. This problem presents significant challenges due to its NP-hard nature and the need for efficient optimization techniques. The contribution of this study lies in the development of an integrated approach that combines constraint programming, a novel heuristic, and Tabu search to provide a comprehensive and efficient solution. The proposed constraint programming model offers exact resolution capabilities, while the heuristic and Tabu search provide approximate solutions, offering a balance between accuracy and efficiency. To enhance the search process, the research introduces effective elimination rules, which reduce the search space and simplify the search effort. This approach improves the overall optimization performance and contributes to finding high-quality solutions. The results demonstrate the effectiveness of the proposed approach. The heuristic approach achieves complete success in solving all instances for specific classes, showcasing its practical applicability. Furthermore, the constraint programming model exhibits exceptional efficiency, successfully solving problems with up to n=500 jobs. This efficiency is noteworthy compared to instances solved by other exact solution approaches, indicating the scalability and effectiveness of the proposed method.

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“…In addition, for a problem with a batch machine followed by a discrete machine, a hybrid membrane computing metaheuristic algorithm was developed in [34] to minimize the makespan. Additionally, there are recent studies considering flow shop problems with various scheduling requirements as well as limited waiting times [35][36][37][38][39][40][41].…”

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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Minimizing the makespan in a flow shop environment under minimum and maximum time-lag constraints

Cited by 16 publications

References 43 publications

Shop scheduling in manufacturing environments: a review

Shop scheduling in manufacturing environments: a review

Makespan Minimization for the Two-Stage Hybrid Flow Shop Problem with Dedicated Machines: A Comprehensive Study of Exact and Heuristic Approaches

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

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