Interactive fuzzy programming based on a probability maximization model for two-level stochastic linear programming problems

In this paper, considering the two‐level linear programming problem, which is a numerical model for the optimization of a hierarchical system by two decisionmakers, we focus on the situation where the coefficients are stochastic variables and reduce the formulated two‐level stochastic linear program...

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Published in:Electronics & communications in Japan. Part 3, Fundamental electronic science Vol. 89; no. 2; pp. 33 - 42
Main Authors: Kato, Kosuke, Katagiri, Hideki, Sakawa, Masatoshi, Wang, Jingtao
Format: Journal Article
Language:English
Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.02.2006
Subjects:
chance constraint
interactive fuzzy programming
probability maximization model
two-level stochastic linear programming problem
ISSN:1042-0967, 1520-6440
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Abstract In this paper, considering the two‐level linear programming problem, which is a numerical model for the optimization of a hierarchical system by two decisionmakers, we focus on the situation where the coefficients are stochastic variables and reduce the formulated two‐level stochastic linear programming problem to an ordinary two‐level programming problem based on the probability maximization model in chance‐constrained programming. Based on the assumption that motivation exists for cooperation between the high‐level decisionmaker and the low‐level decisionmaker in this resulting two‐level programming problem, we consider interactive fuzzy programming that interactively derives a satisfactory solution of the high‐level decisionmaker while considering the balance with the degree of satisfaction of the low‐level decisionmaker. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(2): 33–42, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20166
AbstractList In this paper, considering the two‐level linear programming problem, which is a numerical model for the optimization of a hierarchical system by two decisionmakers, we focus on the situation where the coefficients are stochastic variables and reduce the formulated two‐level stochastic linear programming problem to an ordinary two‐level programming problem based on the probability maximization model in chance‐constrained programming. Based on the assumption that motivation exists for cooperation between the high‐level decisionmaker and the low‐level decisionmaker in this resulting two‐level programming problem, we consider interactive fuzzy programming that interactively derives a satisfactory solution of the high‐level decisionmaker while considering the balance with the degree of satisfaction of the low‐level decisionmaker. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(2): 33–42, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20166
Author Sakawa, Masatoshi
Kato, Kosuke
Wang, Jingtao
Katagiri, Hideki
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References_xml – reference: Zimmermann H-J. Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst 1978;1:45-55.
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– reference: Sakawa M, Nishizaki I, Uemura Y. Interactive fuzzy programming for multilevel linear programming. Comput Math Appl 1998;36:71-86.
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Snippet In this paper, considering the two‐level linear programming problem, which is a numerical model for the optimization of a hierarchical system by two...
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SubjectTerms chance constraint
interactive fuzzy programming
probability maximization model
two-level stochastic linear programming problem
Title Interactive fuzzy programming based on a probability maximization model for two-level stochastic linear programming problems
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