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Jiacai Liu - One of the best experts on this subject based on the ideXlab platform.
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corrections to topsis based Nonlinear Programming methodology for multi attribute decision making with interval valued intuitionistic fuzzy sets apr 10 299 311
IEEE Transactions on Fuzzy Systems, 2018Co-Authors: Jiacai LiuAbstract:There are some mistakes in the computation results of the real example in the article by Li, “TOPSIS-based Nonlinear-Programming methodology for multi-attribute decision making with interval-valued intuitionistic fuzzy sets” [ IEEE Trans. Fuzzy Syst. , vol. 18, no. 2, pp. 299–311, 2010], and this article provides corrections to that paper.
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corrections to topsis based Nonlinear Programming methodology for multi attribute decision making with interval valued intuitionistic fuzzy sets
IEEE Transactions on Fuzzy Systems, 2010Co-Authors: Jiacai LiuAbstract:Interval-valued intuitionistic fuzzy (IVIF) sets are useful to deal with fuzziness inherent in decision data and decision-making processes. The aim of this paper is to develop a Nonlinear-Programming methodology that is based on the technique for order preference by similarity to ideal solution to solve multiattribute decision-making (MADM) problems with both ratings of alternatives on attributes and weights of attributes expressed with IVIF sets. In this methodology, Nonlinear-Programming models are constructed on the basis of the concepts of the relative-closeness coefficient and the weighted-Euclidean distance. Simpler auxiliary Nonlinear-Programming models are further deduced to calculate relative-closeness of IF sets of alternatives to the IVIF-positive ideal solution, which can be used to generate the ranking order of alternatives. The proposed methodology is validated and compared with other similar methods. A real example is examined to demonstrate the applicability and validity of the methodology proposed in this paper.
Shouzhen Zeng - One of the best experts on this subject based on the ideXlab platform.
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interval valued intuitionistic fuzzy multiple attribute decision making based on Nonlinear Programming methodology and topsis method
Information Sciences, 2020Co-Authors: Shyiming Chen, Shouzhen Zeng, Kangyun FanAbstract:Abstract In this paper, we propose a new multiple attribute decision making (MADM) method based on the Nonlinear Programming (NLP) methodology, the TOPSIS method and interval-valued intuitionistic fuzzy values (IVIFVs). The evaluating values of the alternatives with respect to attributes and the attributes’ weights are represented by IVIFVs. The NLP methodology is applied to get the optimal attributes’ weights. The proposed MADM method can overcome the drawbacks of the existing MADM methods to deal with MADM problems using IVIFVs.
Kangyun Fan - One of the best experts on this subject based on the ideXlab platform.
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interval valued intuitionistic fuzzy multiple attribute decision making based on Nonlinear Programming methodology and topsis method
Information Sciences, 2020Co-Authors: Shyiming Chen, Shouzhen Zeng, Kangyun FanAbstract:Abstract In this paper, we propose a new multiple attribute decision making (MADM) method based on the Nonlinear Programming (NLP) methodology, the TOPSIS method and interval-valued intuitionistic fuzzy values (IVIFVs). The evaluating values of the alternatives with respect to attributes and the attributes’ weights are represented by IVIFVs. The NLP methodology is applied to get the optimal attributes’ weights. The proposed MADM method can overcome the drawbacks of the existing MADM methods to deal with MADM problems using IVIFVs.
Shyiming Chen - One of the best experts on this subject based on the ideXlab platform.
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interval valued intuitionistic fuzzy multiple attribute decision making based on Nonlinear Programming methodology and topsis method
Information Sciences, 2020Co-Authors: Shyiming Chen, Shouzhen Zeng, Kangyun FanAbstract:Abstract In this paper, we propose a new multiple attribute decision making (MADM) method based on the Nonlinear Programming (NLP) methodology, the TOPSIS method and interval-valued intuitionistic fuzzy values (IVIFVs). The evaluating values of the alternatives with respect to attributes and the attributes’ weights are represented by IVIFVs. The NLP methodology is applied to get the optimal attributes’ weights. The proposed MADM method can overcome the drawbacks of the existing MADM methods to deal with MADM problems using IVIFVs.
Zdravko Kravanja - One of the best experts on this subject based on the ideXlab platform.
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mixed integer Nonlinear Programming techniques for process systems engineering
Computers & Chemical Engineering, 1995Co-Authors: Ignacio E Grossmann, Zdravko KravanjaAbstract:Abstract This paper presents an overview of mixed-integer Nonlinear Programming techniques by first providing a unified treatment of the Branch and Bound, Outer-Approximation, Generalized Benders and Extended Cutting Plane methods as applied to Nonlinear discrete optimization problems that are expressed in algebraic form. The extension of these methods is also considered for logic based representations. Finally, an overview of the applications in many areas in process engineering is presented.