Scheduling a flowshop problem with fuzzy processing times using ant colony optimization

Sezgın Kiliç; Cengız Kahraman

doi:10.1142/9789812774118_0064

Scheduling a flowshop problem with fuzzy processing times using ant colony optimization

Sezgın Kiliç, Cengız Kahraman

Department of Industrial Engineering

Turkish Air Force Academy

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

1 Citation (Scopus)

Abstract

Most of the work about flowshop problems assumes that the problem data are known exactly at the advance or the common approach to the treatment of the uncertainties in the problem is use of probabilistic models. However, the evaluation and optimization of probabilistic model is computationally expensive and the application of the probabilistic model is rational only when the descriptions of the uncertain parameters are available from the historical data. In this paper we deal with a permutation fiowshop problem with fuzzy processing times. First we explain how to compute start and finish time of each operation on related machines for a given sequence of jobs using fuzzy arithmetic. Next we used a fuzzy ranking method in order to select the best schedule with minimum fuzzy makespan. We proposed an ant colony optimization algorithm for generating and finding good (near optimal) schedules.

Original language	English
Title of host publication	Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006
Editors	Pierre D'Hondt, Etienne E. Kerre, Da Ruan, Martine De Cock, Mike Nachtegael, Paolo F. Fantoni
Publisher	World Scientific Publishing Co. Pte Ltd
Pages	449-456
Number of pages	8
ISBN (Electronic)	9812566902, 9789812566904
DOIs	https://doi.org/10.1142/9789812774118_0064
Publication status	Published - 2006
Event	Applied Artificial Intelligence - 7th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2006 - Genova, Italy Duration: 29 Aug 2006 → 31 Aug 2006

Publication series

Name	Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006

Conference

Conference	Applied Artificial Intelligence - 7th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2006
Country/Territory	Italy
City	Genova
Period	29/08/06 → 31/08/06

Bibliographical note

Publisher Copyright:
© 2006 by World Scientific Publishing Co. Pte. Ltd.

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10.1142/9789812774118_0064

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Kiliç, S., & Kahraman, C. (2006). Scheduling a flowshop problem with fuzzy processing times using ant colony optimization. In P. D'Hondt, E. E. Kerre, D. Ruan, M. De Cock, M. Nachtegael, & P. F. Fantoni (Eds.), Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006 (pp. 449-456). (Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006). World Scientific Publishing Co. Pte Ltd. https://doi.org/10.1142/9789812774118_0064

Kiliç, Sezgın ; Kahraman, Cengız. / Scheduling a flowshop problem with fuzzy processing times using ant colony optimization. Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006. editor / Pierre D'Hondt ; Etienne E. Kerre ; Da Ruan ; Martine De Cock ; Mike Nachtegael ; Paolo F. Fantoni. World Scientific Publishing Co. Pte Ltd, 2006. pp. 449-456 (Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006).

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Kiliç, S & Kahraman, C 2006, Scheduling a flowshop problem with fuzzy processing times using ant colony optimization. in P D'Hondt, EE Kerre, D Ruan, M De Cock, M Nachtegael & PF Fantoni (eds), Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006. Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006, World Scientific Publishing Co. Pte Ltd, pp. 449-456, Applied Artificial Intelligence - 7th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2006, Genova, Italy, 29/08/06. https://doi.org/10.1142/9789812774118_0064

Scheduling a flowshop problem with fuzzy processing times using ant colony optimization. / Kiliç, Sezgın; Kahraman, Cengız.
Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006. ed. / Pierre D'Hondt; Etienne E. Kerre; Da Ruan; Martine De Cock; Mike Nachtegael; Paolo F. Fantoni. World Scientific Publishing Co. Pte Ltd, 2006. p. 449-456 (Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006).

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

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AB - Most of the work about flowshop problems assumes that the problem data are known exactly at the advance or the common approach to the treatment of the uncertainties in the problem is use of probabilistic models. However, the evaluation and optimization of probabilistic model is computationally expensive and the application of the probabilistic model is rational only when the descriptions of the uncertain parameters are available from the historical data. In this paper we deal with a permutation fiowshop problem with fuzzy processing times. First we explain how to compute start and finish time of each operation on related machines for a given sequence of jobs using fuzzy arithmetic. Next we used a fuzzy ranking method in order to select the best schedule with minimum fuzzy makespan. We proposed an ant colony optimization algorithm for generating and finding good (near optimal) schedules.

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Kiliç S, Kahraman C. Scheduling a flowshop problem with fuzzy processing times using ant colony optimization. In D'Hondt P, Kerre EE, Ruan D, De Cock M, Nachtegael M, Fantoni PF, editors, Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006. World Scientific Publishing Co. Pte Ltd. 2006. p. 449-456. (Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006). doi: 10.1142/9789812774118_0064

Scheduling a flowshop problem with fuzzy processing times using ant colony optimization

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