Fuzzy decision making under uncertainty

Cengiz Kahraman; Ethem Tolga

doi:10.1007/3-540-64582-9_756

Fuzzy decision making under uncertainty

Cengiz Kahraman
, Ethem Tolga

Endüstri Mühendisliği Bölümü

Galatasaray University

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

1 Atıf (Scopus)

Özet

When no probabilities are available for states of nature, decisions are given under uncertainty. When probabilities are unattainable, the criteria such as minimax, maximin, minimaxregret can be used. While these criteria are used, a single value is assigned for every strategy and state of nature. Fuzzy numbers are a good tool for the operation research analyst facing uncertainty and subjectivity. A triangular fuzzy number has been used instead of a single value of outcome. Numerical Examples have been given for every fuzzy decision criterion.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Methodology and Tools in Knowledge-Based Systems - 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-1998-AIE, Proceedings
Editörler	Jose Mira, Angel Pasqual del Pobil, Moonis Ali
Yayınlayan	Springer Verlag
Sayfalar	263-271
Sayfa sayısı	9
ISBN (Basılı)	3540645829, 9783540645825
DOI'lar	https://doi.org/10.1007/3-540-64582-9_756
Yayın durumu	Yayınlandı - 1998
Etkinlik	11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1998 - Benicassim, Spain Süre: 1 Haz 1998 → 4 Haz 1998

Yayın serisi

Adı	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Hacim	1415
ISSN (Basılı)	0302-9743
ISSN (Elektronik)	1611-3349

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

???event.eventtypes.event.conference???	11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1998
Ülke/Bölge	Spain
Şehir	Benicassim
Periyot	1/06/98 → 4/06/98

Bibliyografik not

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1998.

Belgeye Erişim

10.1007/3-540-64582-9_756

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Kahraman, C., & Tolga, E. (1998). Fuzzy decision making under uncertainty. In J. Mira, A. P. del Pobil, & M. Ali (Eds.), Methodology and Tools in Knowledge-Based Systems - 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-1998-AIE, Proceedings (pp. 263-271). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Hac. 1415). Springer Verlag. https://doi.org/10.1007/3-540-64582-9_756

Kahraman, Cengiz ; Tolga, Ethem. / Fuzzy decision making under uncertainty. Methodology and Tools in Knowledge-Based Systems - 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-1998-AIE, Proceedings. editör / Jose Mira ; Angel Pasqual del Pobil ; Moonis Ali. Springer Verlag, 1998. pp. 263-271 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Fuzzy decision making under uncertainty",

abstract = "When no probabilities are available for states of nature, decisions are given under uncertainty. When probabilities are unattainable, the criteria such as minimax, maximin, minimaxregret can be used. While these criteria are used, a single value is assigned for every strategy and state of nature. Fuzzy numbers are a good tool for the operation research analyst facing uncertainty and subjectivity. A triangular fuzzy number has been used instead of a single value of outcome. Numerical Examples have been given for every fuzzy decision criterion.",

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author = "Cengiz Kahraman and Ethem Tolga",

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Kahraman, C & Tolga, E 1998, Fuzzy decision making under uncertainty. in J Mira, AP del Pobil & M Ali (eds), Methodology and Tools in Knowledge-Based Systems - 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-1998-AIE, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), hac. 1415, Springer Verlag, pp. 263-271, 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1998, Benicassim, Spain, 1/06/98. https://doi.org/10.1007/3-540-64582-9_756

Fuzzy decision making under uncertainty. / Kahraman, Cengiz; Tolga, Ethem.
Methodology and Tools in Knowledge-Based Systems - 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-1998-AIE, Proceedings. ed. / Jose Mira; Angel Pasqual del Pobil; Moonis Ali. Springer Verlag, 1998. p. 263-271 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Hac. 1415).

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

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N2 - When no probabilities are available for states of nature, decisions are given under uncertainty. When probabilities are unattainable, the criteria such as minimax, maximin, minimaxregret can be used. While these criteria are used, a single value is assigned for every strategy and state of nature. Fuzzy numbers are a good tool for the operation research analyst facing uncertainty and subjectivity. A triangular fuzzy number has been used instead of a single value of outcome. Numerical Examples have been given for every fuzzy decision criterion.

AB - When no probabilities are available for states of nature, decisions are given under uncertainty. When probabilities are unattainable, the criteria such as minimax, maximin, minimaxregret can be used. While these criteria are used, a single value is assigned for every strategy and state of nature. Fuzzy numbers are a good tool for the operation research analyst facing uncertainty and subjectivity. A triangular fuzzy number has been used instead of a single value of outcome. Numerical Examples have been given for every fuzzy decision criterion.

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Kahraman C, Tolga E. Fuzzy decision making under uncertainty. In Mira J, del Pobil AP, Ali M, editörler, Methodology and Tools in Knowledge-Based Systems - 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-1998-AIE, Proceedings. Springer Verlag. 1998. p. 263-271. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-64582-9_756

Fuzzy decision making under uncertainty

Özet

Yayın serisi

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Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

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