A two-level method of production planning and scheduling for bi-objective reentrant hybrid flow shops

Cho, Hang-Min; Jeong, In-Jae

doi:10.1016/j.cie.2017.02.010

Cited by 38 publications

(12 citation statements)

References 19 publications

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“…In consequence, the PFS approach becomes constructive for systems with more than three machines [24]. This analysis is being refined by newer results (Tab.…”

Section: Permutation and Non-permutation Complexity: Special Casesmentioning

confidence: 99%

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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“…In consequence, the PFS approach becomes constructive for systems with more than three machines [24]. This analysis is being refined by newer results (Tab.…”

Section: Permutation and Non-permutation Complexity: Special Casesmentioning

confidence: 99%

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

2021

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“…Lin and Chen (2015) presents a simulation optimisation approach for a hybrid flow shop scheduling problem in a real-world semiconductor back-end assembly facility. In recent years, there is study which demonstrates the value of• the simulation optimisation approach for practical applications and provides directions for future research on the stochastic hybrid flow shop scheduling problem (Cho and Jeong, 2017;Li et aI., 2015;Chamnanlor et aI., 2015). Research on the scheduling problem of semiconductor wafer fabrication and propose a new dispatching rule based on the load balance.…”

Section: Literature Reviewmentioning

confidence: 99%

Improved heuristic algorithm for modern industrial production scheduling

Jiang

Pan

2018

IJMIC

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Scheduling is one of the core links of modem industrial production. Scheduling needs to be designed according to the characteristics of the production line. In order to optimise the problem of workshop scheduling, the service-oriented programming idea and advanced technology to optimise the system development of mixed flow shop are adopted. The system is designed for applications in a distributed network environment. In this paper, an improved heuristic industrial production scheduling method is proposed to solve the scheduling system problem with multiple scheduling tasks, multiple processes, multiple stations, multiple constraints and rules. This method specifies the processing equipment, start tim.eand completion time for each process of the production task. The application methadshows that the proposed method can improve the automation and intelligence level of the scheduling process, improve the utilisation rate of equipment and other production resources, and give full play to the enterprise production capacity.

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“…Traditional inventory models [1][2][3][4] and production planning models [5][6][7] involve deterministic constrained functions and/or objective functions in deterministic environments. Nevertheless, uncertainty is nearly universal in real world.…”

Section: Introductionmentioning

confidence: 99%

Neutrosophic Number Optimization Models and Their Application in the Practical Production Process

Wang

2021

Journal of Mathematics

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In order to simplify the complex calculation and solve the difficult solution problems of neutrosophic number optimization models (NNOMs) in the practical production process, this paper presents two methods to solve NNOMs, where Matlab built-in function “fmincon()” and neutrosophic number operations (NNOs) are used in indeterminate environments. Next, the two methods are applied to linear and nonlinear programming problems with neutrosophic number information to obtain the optimal solution of the maximum/minimum objective function under the constrained conditions of practical productions by neutrosophic number optimization programming (NNOP) examples. Finally, under indeterminate environments, the fit optimal solutions of the examples can also be achieved by using some specified indeterminate scales to fulfill some specified actual requirements. The NNOP methods can obtain the feasible and flexible optimal solutions and indicate the advantage of simple calculations in practical applications.

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A two-level method of production planning and scheduling for bi-objective reentrant hybrid flow shops

Cited by 38 publications

References 19 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

Improved heuristic algorithm for modern industrial production scheduling

Neutrosophic Number Optimization Models and Their Application in the Practical Production Process

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