Results 221 to 230 of about 31,194 (261)
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On Possibilistic/Fuzzy Optimization
2007We focus on possibilistic/fuzzy optimality in the framework of mathematical programming problem with a possibilistic objective function. We observe the interaction between possibilistic objective function values. Two optimality concepts, possible and necessary optimalities are reviewed. The necessary soft optimality is investigated.
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Fuzzy optimization of logistic processes
2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291), 2003This paper addresses the problem of optimizing logistic processes that can be modeled as birth and death processes. A fuzzy decision making algorithm is proposed to dynamically assign components to orders. This algorithm tries to minimize the overall delivery delays and, at the same type, prefers orders with high priorities.
J. M. Sousa +3 more
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2013
Fuzzy set theory has a strong track record of success in the field of Optimization under uncertainty. It offers a proper framework for coming to grips with situations where imprecision and complexity are in the state of affairs in an Optimization setting.
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Fuzzy set theory has a strong track record of success in the field of Optimization under uncertainty. It offers a proper framework for coming to grips with situations where imprecision and complexity are in the state of affairs in an Optimization setting.
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Fuzzy controlled simulation optimization
Fuzzy Sets and Systems, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Andrés L. Medaglia +2 more
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On the optimization of fuzzy decision trees
Fuzzy Sets and Systems, 2000The induction of fuzzy decision trees is an important way of acquiring imprecise knowledge automatically. Fuzzy ID3 and its variants are popular and efficient methods of making fuzzy decision trees from a group of training examples. This paper points out the inherent defect of the likes of Fuzzy ID3, presents two optimization principles of fuzzy ...
Xizhao Wang +3 more
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Fuzzy Portfolio Optimization Model with Fuzzy Numbers
2011A new portfolio optimization model with triangular fuzzy numbers is proposed in this paper. The objective function is considered as maximizing fuzzy expected return of securities under the constraint that the risk will not be greater than a preset tolerable fuzzy number, where the expected return and risk of securities are described as triangular fuzzy
Chunquan Li 0003, Jianhua Jin
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Unsupervised optimal fuzzy clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989This study reports on a method for carrying out fuzzy classification without a priori assumptions on the number of clusters in the data set. Assessment of cluster validity is based on performance measures using hypervolume and density criteria. An algorithm is derived from a combination of the fuzzy K-means algorithm and fuzzy maximum-likelihood ...
Isak Gath, Amir B. Geva
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Fuzzy Optimal Control for Multistage Fuzzy Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2011In the case that a system is affected by fuzzy factors, a fuzzy optimal-control problem is proposed. A fuzzy optimal-control problem for a multistage fuzzy system is considered to optimize the expected value of a fuzzy objective function subject to a multistage fuzzy system where, at every stage, the system is disturbed by a fuzzy variable.
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On fuzzy convexity and parametric fuzzy optimization
Fuzzy Sets and Systems, 1992The authors make a very interesting study on different types of convexity and generalized convexity of fuzzy sets. The concept of convexity is applied in order to formulate the general fuzzy nonlinear programming problem.
Ammar, Elsaid, Metz, Joachim
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Interval Methods and Fuzzy Optimization
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 1997In this paper, we describe interval-based methods for solving constrained fuzzy optimization problems. The class of fuzzy functions we consider for the optimization problems is the set of real-valued functions where one or more parameters/coefficients are fuzzy numbers.
Weldon A. Lodwick, K. David Jamison
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