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Titlebook: Large Scale Interactive Fuzzy Multiobjective Programming; Decomposition Approa Masatoshi Sakawa Book 2000 Springer-Verlag Berlin Heidelberg

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發(fā)表于 2025-3-21 16:31:10 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Large Scale Interactive Fuzzy Multiobjective Programming
副標(biāo)題Decomposition Approa
編輯Masatoshi Sakawa
視頻videohttp://file.papertrans.cn/582/581357/581357.mp4
叢書(shū)名稱Studies in Fuzziness and Soft Computing
圖書(shū)封面Titlebook: Large Scale Interactive Fuzzy Multiobjective Programming; Decomposition Approa Masatoshi Sakawa Book 2000 Springer-Verlag Berlin Heidelberg
描述Simultaneous considerations of multiobjectiveness, fuzziness and block angular structures involved in the real-world decision making problems lead us to the new field of interactive multiobjective optimization for large scale programming problems under fuzziness. The aim of this book is to introduce the latest advances in the new field of interactive multiobjective optimization for large scale programming problems under fuzziness on the basis of the author‘s continuing research. Special stress is placed on interactive decision making aspects of fuzzy multiobjective optimization for human-centered systems in most realistic situations when dealing with fuzziness. The book is intended for graduate students, researchers and practitioners in the fields of operations research, industrial engineering, management science and computer science.
出版日期Book 2000
關(guān)鍵詞Operations Research; algorithm; algorithms; decision making; decision support; fuzziness; fuzzy logic; fuzz
版次1
doihttps://doi.org/10.1007/978-3-7908-1851-2
isbn_softcover978-3-662-00386-2
isbn_ebook978-3-7908-1851-2Series ISSN 1434-9922 Series E-ISSN 1860-0808
issn_series 1434-9922
copyrightSpringer-Verlag Berlin Heidelberg 2000
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沙發(fā)
發(fā)表于 2025-3-21 21:04:28 | 只看該作者
Mathematical Preliminaries,ent, called fuzzy decision, is then examined. Fundamental notions and methods of multiobjective, interactive multiobjective, and interactive fuzzy multiobjective linear programming are briefly reviewed. A brief discussion of genetic algorithms is also given.
板凳
發(fā)表于 2025-3-22 03:18:35 | 只看該作者
,Large Scale Fuzzy Multiobjective 0–1 Programming,pter 7, interactive fuzzy multiobjective 0–1 programming as well as fuzzy multiobjective 0–1 programming, both proposed by the authors, are explained in detail together with several numerical experiments.
地板
發(fā)表于 2025-3-22 05:57:28 | 只看該作者
,Large Scale Interactive Multiobjective 0–1 Programming with Fuzzy Numbers,ition procedures, both without and with the fuzzy goals of the decision maker, for deriving a satisficing solution efficiently from an extended Pareto optimal solution set are presented. Several numerical experiments are also given.
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發(fā)表于 2025-3-22 09:09:44 | 只看該作者
6#
發(fā)表于 2025-3-22 14:42:59 | 只看該作者
Book 2000red systems in most realistic situations when dealing with fuzziness. The book is intended for graduate students, researchers and practitioners in the fields of operations research, industrial engineering, management science and computer science.
7#
發(fā)表于 2025-3-22 18:10:06 | 只看該作者
1434-9922 uman-centered systems in most realistic situations when dealing with fuzziness. The book is intended for graduate students, researchers and practitioners in the fields of operations research, industrial engineering, management science and computer science.978-3-662-00386-2978-3-7908-1851-2Series ISSN 1434-9922 Series E-ISSN 1860-0808
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發(fā)表于 2025-3-22 21:36:28 | 只看該作者
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發(fā)表于 2025-3-23 01:32:33 | 只看該作者
Large Scale Fuzzy Linear Programming, is shown that the formulated problem can be reduced to a number of independent linear subproblems and the satisficing solution for the decision maker is directly obtained just only by solving the subproblems. Moreover, even if the appropriate conditions are not satisfied, it is shown that the Dantzig-Wolfe decomposition method is applicable.
10#
發(fā)表于 2025-3-23 08:18:34 | 只看該作者
Large Scale Fuzzy Multiobjective Linear Programming,or obtaining the satisficing solution for the decision maker. Interactive fuzzy multiobjective linear programming for deriving the satisficing solution for the decision maker by updating the reference membership levels is also presented by utilizing the Dantzig-Wolfe decomposition method.
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