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

Endüstri Mühendisliği Bölümü

Turkish Air Force Academy

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

1 Atıf (Scopus)

Özet

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.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006
Editörler	Pierre D'Hondt, Etienne E. Kerre, Da Ruan, Martine De Cock, Mike Nachtegael, Paolo F. Fantoni
Yayınlayan	World Scientific Publishing Co. Pte Ltd
Sayfalar	449-456
Sayfa sayısı	8
ISBN (Elektronik)	9812566902, 9789812566904
DOI'lar	https://doi.org/10.1142/9789812774118_0064
Yayın durumu	Yayınlandı - 2006
Etkinlik	Applied Artificial Intelligence - 7th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2006 - Genova, Italy Süre: 29 Ağu 2006 → 31 Ağu 2006

Yayın serisi

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

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	Applied Artificial Intelligence - 7th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2006
Ülke/Bölge	Italy
Şehir	Genova
Periyot	29/08/06 → 31/08/06

Bibliyografik not

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

Belgeye Erişim

10.1142/9789812774118_0064

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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. editör / 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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title = "Scheduling a flowshop problem with fuzzy processing times using ant colony optimization",

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.",

author = "Sezgın Kili{\c c} and Cengız Kahraman",

note = "Publisher Copyright: {\textcopyright} 2006 by World Scientific Publishing Co. Pte. Ltd.; Applied Artificial Intelligence - 7th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2006 ; Conference date: 29-08-2006 Through 31-08-2006",

year = "2006",

doi = "10.1142/9789812774118\_0064",

language = "English",

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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).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

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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, editörler, 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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Belgeye Erişim

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