Flexible job shop scheduling problem for parallel batch processing machine with compatible job families

Ham, Andy

doi:10.1016/j.apm.2016.12.034

Cited by 37 publications

(17 citation statements)

References 26 publications

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“…Based on the amount to produce for each commodity, we first generate sufficient number of recipe instances for each recipe type. The number of instances for a given recipe γ j can be determined using equation (2). For instance, a requirement of 45 tonnes of "Std Weiss" would lead to 5 instances of γ 1 and 4 instances of γ 2 , γ 3 and γ 4 , respectively.…”

Section: Resultsmentioning

confidence: 99%

“…Numerous versions of this problem have been proposed, starting from an original Job-shop Scheduling Problem (JSP) coined by R.L. Graham in 1996, and including flexible JSP (FJSP), where operations can be processed on any compatible resource [2]. However, the classic JSP and its popular extensions are limited to certain classes of rather artificial problems and do not scale well to the problem sizes found in industry [3].…”

Section: Introductionmentioning

confidence: 99%

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Solving the Multi-objective Flexible Job-Shop Scheduling Problem with Alternative Recipes for a Chemical Production Process

Dziurzański

Zhao

Swan

et al. 2019

Applications of Evolutionary Computation

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This paper considers a new variant of a multi-objective flexible job-shop scheduling problem, featuring multisubset selection of manufactured recipes. We propose a novel associated chromosome encoding and customise the classic MOEA/D multi-objective genetic algorithm with new genetic operators. The applicability of the proposed approach is evaluated experimentally and showed to outperform typical multiobjective genetic algorithms. The problem variant is motivated by realworld manufacturing in a chemical plant and is applicable to other plants that manufacture goods using alternative recipes.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Solving the Multi-objective Flexible Job-Shop Scheduling Problem with Alternative Recipes for a Chemical Production Process

Dziurzański

Zhao

Swan

et al. 2019

Applications of Evolutionary Computation

View full text Add to dashboard Cite

show abstract

“…Constraints (14) and (15) define the and as binary variables. Constraints (16), (17), and 18 are non-negativity constraints.…”

Section: Decision Variablesmentioning

confidence: 99%

“…Ham [16] introduced a mathematical model for FJSP with PBM with the objective of minimizing the maximum computational time.…”

Section: Baez Et Almentioning

confidence: 99%

Bir Uygulama: Bir Beyaz Eşya Üretim Firmasının Boyahane Bölümünde Paralel Makineler için Sıraya Bağlı Kurulum Sürelerini içeren bir Model

Kasimoğlu

Demir

Yaz

et al. 2021

Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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Excessive buffer inventory may disrupt production and constitute one of the main problems. One of the ways of coping with the inventory problems in the mass production lines is to achieve and implement a detailed production schedule. In this study, a company with a mass production line in the die house station of a white goods sector is in consideration. A mixed-integer programming model with sequence-dependent setup times has been developed to solve the excessive work in process problems for the dye house station. The developed model has been applied to the company to test the model by using real data and the problem has been solved by using the General Algebraic Modeling System (GAMS) CPLEX 24,1 solver. The optimal solution is obtained in 10 hours and 3 minutes. In the solution, the total earliness and tardiness time for 30 jobs is 4299 minutes.

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“…Manufacturing processes' scheduling is often modelled using Job-shop Scheduling Problem (JSP), an optimisation problem whose purpose is to determine allocation of manufacturing jobs to the available resources at particular times to optimise certain key objectives, for example, the total manufacturing time aka makespan [7]. Due to its practical applications, the research related to JSP has been conducted by numerous researchers [1] and assorted variants of this problem have been introduced to describe realworld scenarios.…”

Section:  Introductionmentioning

confidence: 99%

Process planning and scheduling optimisation with alternative recipes

Dziurzański

Zhao

Scholze

et al. 2020

At - Automatisierungstechnik

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This paper considers an application of a new variant of a multi-objective flexible job-shop scheduling problem, featuring multisubset selection of manufactured recipes, to a real-world chemical plant. The problem is optimised using a multi-objective genetic algorithm with customised mutation and elitism operators that minimises both the total production time and the produced commodity surplus. The algorithm evaluation is performed with both random and historic manufacturing orders. The latter demonstrated that the proposed system can lead to more than 10 % makespan improvements in comparison with human operators.

show abstract

Flexible job shop scheduling problem for parallel batch processing machine with compatible job families

Cited by 37 publications

References 26 publications

Solving the Multi-objective Flexible Job-Shop Scheduling Problem with Alternative Recipes for a Chemical Production Process

Solving the Multi-objective Flexible Job-Shop Scheduling Problem with Alternative Recipes for a Chemical Production Process

Bir Uygulama: Bir Beyaz Eşya Üretim Firmasının Boyahane Bölümünde Paralel Makineler için Sıraya Bağlı Kurulum Sürelerini içeren bir Model

Process planning and scheduling optimisation with alternative recipes

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