Fuzzy Economic Order Quantity Model With Ranking Fuzzy Number Cost Parameters
Nirmal Kumar Mandal (2012)
The Yugoslav Journal of Operations Research
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Nirmal Kumar Mandal (2012)
The Yugoslav Journal of Operations Research
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Banerjee, S., Roy, T.K. (2010)
Advances in Operations Research
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Slobodan Vujić, Goran Ćirović (1996)
The Yugoslav Journal of Operations Research
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Yoshiki Uemura (2006)
Control and Cybernetics
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S. Kar, T. Roy, M. Maiti (2001)
The Yugoslav Journal of Operations Research
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Danijela Tadić (2005)
The Yugoslav Journal of Operations Research
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Collan, Mikael, Fullér, Robert, Mezei, József (2009)
Journal of Applied Mathematics and Decision Sciences
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Bogdana Stanojević, Milan Stanojević (2009)
The Yugoslav Journal of Operations Research
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Milanka Gardašević-Filipović, Dragan Z. Šaletić (2010)
The Yugoslav Journal of Operations Research
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Branko Tadić, Danijela Tadić, Nenad Marjanović (2007)
The Yugoslav Journal of Operations Research
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Mahmod Othman, Ku Ruhana Ku-Mahamud, Azuraliza Abu Bakar (2008)
The Yugoslav Journal of Operations Research
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Mariano Jiménez López, María Victoria Rodríguez Uría, María del Mar Arenas Parra, Amelia Bilbao Terol (2000)
Mathware and Soft Computing
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In this paper we propose a method to solve a linear programming problem involving fuzzy parameters whose possibility distributions are given by fuzzy numbers. To address the above problem we have used a preference relationship of fuzzy numbers that leads us to a solving method that produces the so-called α-degree feasible solutions. It must be pointed out that the final solution of the problem depends critically on this degree of feasibility, which is in conflict with the optimal value...
Vojtěch Sukač, Jana Talašová, Jan Stoklasa (2016)
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
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The paper introduces a new method of reaching a consensus in multiple criteria group decision-making under fuzziness. This model is based on the general definition of the ‘soft’ consensus introduced by Kacprzyk and Fedrizzi in 1986. The fuzzy evaluations of alternatives express degrees of fulfillment of the given goals by the respective alternatives for each expert. The selection of the best alternative is based on the fuzzy consensus by experts. For this purpose a set of alternatives...
Jiří Močkoř (1997)
Acta Mathematica et Informatica Universitatis Ostraviensis
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