An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company

Ali Ozan Özkul; Gamze Küçük; Ceren Çelik; Nevzatcem Öztuna; Mert Demirkan; Ezgi Çağlar Nizam; Yıldırımşan Büyükmertoğlu; Damla Yüksel; Ayhan Özgür Toy

doi:10.1007/978-3-030-62784-3_68

An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company

Ali Ozan Özkul, Gamze Küçük, Ceren Çelik, Nevzatcem Öztuna, Mert Demirkan, Ezgi Çağlar Nizam, Yıldırımşan Büyükmertoğlu, Damla Yüksel^*, Ayhan Özgür Toy

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

In this study, we consider the flexible job-shop scheduling problem at a local metal sheet processing company. We aim to develop a model and an algorithm to generate a weekly production plan for the company. The objective is to minimize the makespan while meeting the demands of products for a given planning horizon. First, we provide an LP formulation of this problem. The computational complexity of the problem is NP-hard, hence the input data prohibits obtaining the optimal solution in a reasonable time. Therefore, we implement a metaheuristic and several rule-based heuristics. These are Genetic Algorithm, Giffler and Thompson’s Algorithm, and three other Rule-Based Heuristic Algorithms that we developed. We first test our model and heuristics over a set of sample instances, then we solve for the real data. Our experimental study indicates that one of the rule-based heuristics we developed outperforms others in most of the instances.

Original language	English
Title of host publication	Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey
Editors	Numan M. Durakbasa, M. Güneş Gençyılmaz
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	817-830
Number of pages	14
ISBN (Print)	9783030627836
DOIs	https://doi.org/10.1007/978-3-030-62784-3_68
Publication status	Published - 2021
Externally published	Yes
Event	International Symposium for Production Research, ISPR 2020 - Antalya, Turkey Duration: 24 Sept 2020 → 26 Sept 2020

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	International Symposium for Production Research, ISPR 2020
Country/Territory	Turkey
City	Antalya
Period	24/09/20 → 26/09/20

Bibliographical note

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Decision support system
Flexible job-shop scheduling
Genetic algorithm
Giffler and Thompson’s Algorithm
Meta-heuristics
Optimization

Access to Document

10.1007/978-3-030-62784-3_68

Persistent URL (handle)

Persistent link

Cite this

Özkul, A. O., Küçük, G., Çelik, C., Öztuna, N., Demirkan, M., Nizam, E. Ç., Büyükmertoğlu, Y., Yüksel, D., & Toy, A. Ö. (2021). An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company. In N. M. Durakbasa, & M. G. Gençyılmaz (Eds.), Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey (pp. 817-830). (Lecture Notes in Mechanical Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-62784-3_68

Özkul, Ali Ozan ; Küçük, Gamze ; Çelik, Ceren et al. / An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company. Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey. editor / Numan M. Durakbasa ; M. Güneş Gençyılmaz. Springer Science and Business Media Deutschland GmbH, 2021. pp. 817-830 (Lecture Notes in Mechanical Engineering).

@inproceedings{95a3181997654352a599f0aff3004f7f,

title = "An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company",

abstract = "In this study, we consider the flexible job-shop scheduling problem at a local metal sheet processing company. We aim to develop a model and an algorithm to generate a weekly production plan for the company. The objective is to minimize the makespan while meeting the demands of products for a given planning horizon. First, we provide an LP formulation of this problem. The computational complexity of the problem is NP-hard, hence the input data prohibits obtaining the optimal solution in a reasonable time. Therefore, we implement a metaheuristic and several rule-based heuristics. These are Genetic Algorithm, Giffler and Thompson{\textquoteright}s Algorithm, and three other Rule-Based Heuristic Algorithms that we developed. We first test our model and heuristics over a set of sample instances, then we solve for the real data. Our experimental study indicates that one of the rule-based heuristics we developed outperforms others in most of the instances.",

keywords = "Decision support system, Flexible job-shop scheduling, Genetic algorithm, Giffler and Thompson{\textquoteright}s Algorithm, Meta-heuristics, Optimization",

author = "{\"O}zkul, \{Ali Ozan\} and Gamze K{\"u}{\c c}{\"u}k and Ceren {\c C}elik and Nevzatcem {\"O}ztuna and Mert Demirkan and Nizam, \{Ezgi {\c C}ağlar\} and Yıldırım{\c s}an B{\"u}y{\"u}kmertoğlu and Damla Y{\"u}ksel and Toy, \{Ayhan {\"O}zg{\"u}r\}",

note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Symposium for Production Research, ISPR 2020 ; Conference date: 24-09-2020 Through 26-09-2020",

year = "2021",

doi = "10.1007/978-3-030-62784-3\_68",

language = "English",

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editor = "Durakbasa, \{Numan M.\} and Gen{\c c}yılmaz, \{M. G{\"u}ne{\c s}\}",

booktitle = "Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey",

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Özkul, AO, Küçük, G, Çelik, C, Öztuna, N, Demirkan, M, Nizam, EÇ, Büyükmertoğlu, Y, Yüksel, D & Toy, AÖ 2021, An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company. in NM Durakbasa & MG Gençyılmaz (eds), Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey. Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH, pp. 817-830, International Symposium for Production Research, ISPR 2020, Antalya, Turkey, 24/09/20. https://doi.org/10.1007/978-3-030-62784-3_68

An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company. / Özkul, Ali Ozan; Küçük, Gamze; Çelik, Ceren et al.
Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey. ed. / Numan M. Durakbasa; M. Güneş Gençyılmaz. Springer Science and Business Media Deutschland GmbH, 2021. p. 817-830 (Lecture Notes in Mechanical Engineering).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AU - Özkul, Ali Ozan

AU - Küçük, Gamze

AU - Çelik, Ceren

AU - Öztuna, Nevzatcem

AU - Demirkan, Mert

AU - Nizam, Ezgi Çağlar

AU - Büyükmertoğlu, Yıldırımşan

AU - Yüksel, Damla

AU - Toy, Ayhan Özgür

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N2 - In this study, we consider the flexible job-shop scheduling problem at a local metal sheet processing company. We aim to develop a model and an algorithm to generate a weekly production plan for the company. The objective is to minimize the makespan while meeting the demands of products for a given planning horizon. First, we provide an LP formulation of this problem. The computational complexity of the problem is NP-hard, hence the input data prohibits obtaining the optimal solution in a reasonable time. Therefore, we implement a metaheuristic and several rule-based heuristics. These are Genetic Algorithm, Giffler and Thompson’s Algorithm, and three other Rule-Based Heuristic Algorithms that we developed. We first test our model and heuristics over a set of sample instances, then we solve for the real data. Our experimental study indicates that one of the rule-based heuristics we developed outperforms others in most of the instances.

AB - In this study, we consider the flexible job-shop scheduling problem at a local metal sheet processing company. We aim to develop a model and an algorithm to generate a weekly production plan for the company. The objective is to minimize the makespan while meeting the demands of products for a given planning horizon. First, we provide an LP formulation of this problem. The computational complexity of the problem is NP-hard, hence the input data prohibits obtaining the optimal solution in a reasonable time. Therefore, we implement a metaheuristic and several rule-based heuristics. These are Genetic Algorithm, Giffler and Thompson’s Algorithm, and three other Rule-Based Heuristic Algorithms that we developed. We first test our model and heuristics over a set of sample instances, then we solve for the real data. Our experimental study indicates that one of the rule-based heuristics we developed outperforms others in most of the instances.

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KW - Flexible job-shop scheduling

KW - Genetic algorithm

KW - Giffler and Thompson’s Algorithm

KW - Meta-heuristics

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BT - Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey

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Özkul AO, Küçük G, Çelik C, Öztuna N, Demirkan M, Nizam EÇ et al. An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company. In Durakbasa NM, Gençyılmaz MG, editors, Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey. Springer Science and Business Media Deutschland GmbH. 2021. p. 817-830. (Lecture Notes in Mechanical Engineering). doi: 10.1007/978-3-030-62784-3_68

An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company

Abstract

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Bibliographical note

Keywords

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