A scatter search method for multiobjective fuzzy permutation flow shop scheduling problem: A real world application

Orhan Engin; Cengiz Kahraman; Mustafa Kerim Yilmaz

doi:10.1007/978-3-642-02836-6_6

A scatter search method for multiobjective fuzzy permutation flow shop scheduling problem: A real world application

Orhan Engin^*
, Cengiz Kahraman
, Mustafa Kerim Yilmaz

^*Bu çalışma için yazışmadan sorumlu yazar

Endüstri Mühendisliği Bölümü

Selcuk University

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

19 Atıf (Scopus)

Özet

In this chapter, a scatter search (SS) method is proposed to solve the multiobjective permutation fuzzy flow shop scheduling problem. The objectives are minimizing the average tardiness and the number of tardy jobs. The developed scatter search method is tested on real-world data collected at an engine piston manufacturing company. Using the proposed SS algorithm, the best set of parameters is used to obtain the optimal or near optimal solutions of multiobjective fuzzy flow shop scheduling problem in the shortest time. These parameters are determined by full factorial design of experiments (DOE). The feasibility and effectiveness of the proposed scatter search method is demonstrated by comparing it with the hybrid genetic algorithm (HGA).

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Computational Intelligence in Flow Shop and Job Shop Scheduling
Editörler	Uday Chakraborty
Sayfalar	169-189
Sayfa sayısı	21
DOI'lar	https://doi.org/10.1007/978-3-642-02836-6_6
Yayın durumu	Yayınlandı - 2009

Yayın serisi

Adı	Studies in Computational Intelligence
Hacim	230
ISSN (Basılı)	1860-949X

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

SKH 9 Sanayi, Yenilikçilik ve Altyapı

Belgeye Erişim

10.1007/978-3-642-02836-6_6

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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abstract = "In this chapter, a scatter search (SS) method is proposed to solve the multiobjective permutation fuzzy flow shop scheduling problem. The objectives are minimizing the average tardiness and the number of tardy jobs. The developed scatter search method is tested on real-world data collected at an engine piston manufacturing company. Using the proposed SS algorithm, the best set of parameters is used to obtain the optimal or near optimal solutions of multiobjective fuzzy flow shop scheduling problem in the shortest time. These parameters are determined by full factorial design of experiments (DOE). The feasibility and effectiveness of the proposed scatter search method is demonstrated by comparing it with the hybrid genetic algorithm (HGA).",

author = "Orhan Engin and Cengiz Kahraman and Yilmaz, \{Mustafa Kerim\}",

year = "2009",

doi = "10.1007/978-3-642-02836-6\_6",

language = "English",

isbn = "9783642028359",

series = "Studies in Computational Intelligence",

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editor = "Uday Chakraborty",

booktitle = "Computational Intelligence in Flow Shop and Job Shop Scheduling",

}

A scatter search method for multiobjective fuzzy permutation flow shop scheduling problem: A real world application. / Engin, Orhan; Kahraman, Cengiz; Yilmaz, Mustafa Kerim.
Computational Intelligence in Flow Shop and Job Shop Scheduling. ed. / Uday Chakraborty. 2009. p. 169-189 (Studies in Computational Intelligence; Hac. 230).

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

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AU - Kahraman, Cengiz

AU - Yilmaz, Mustafa Kerim

PY - 2009

Y1 - 2009

N2 - In this chapter, a scatter search (SS) method is proposed to solve the multiobjective permutation fuzzy flow shop scheduling problem. The objectives are minimizing the average tardiness and the number of tardy jobs. The developed scatter search method is tested on real-world data collected at an engine piston manufacturing company. Using the proposed SS algorithm, the best set of parameters is used to obtain the optimal or near optimal solutions of multiobjective fuzzy flow shop scheduling problem in the shortest time. These parameters are determined by full factorial design of experiments (DOE). The feasibility and effectiveness of the proposed scatter search method is demonstrated by comparing it with the hybrid genetic algorithm (HGA).

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BT - Computational Intelligence in Flow Shop and Job Shop Scheduling

A2 - Chakraborty, Uday

ER -

A scatter search method for multiobjective fuzzy permutation flow shop scheduling problem: A real world application

Özet

Yayın serisi

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

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