Large Scale Interactive Multiobjective 0–1 Programming with Fuzzy Numbers

2000 ◽  
pp. 149-171
Author(s):  
Masatoshi Sakawa
Keyword(s):  
Large Scale ◽  
Fuzzy Numbers

scholarly journals An interactive algorithm for large scale multiple objective programming problems with fuzzy parameters through TOPSIS approach

2011 ◽  
Vol 21 (2) ◽  
pp. 253-273 ◽  
Author(s):  
Mahmoud Abo-Sinna ◽  
Tarek Abou-El-Enien
Keyword(s):  
Pareto Optimality ◽  
Large Scale ◽  
Fuzzy Numbers ◽  
Multiple Objective Programming ◽  
Multiple Objective ◽  
Fuzzy Decision Making ◽  
Interactive Algorithm ◽  
Objective Programming ◽  
Topsis Approach ◽  
Fuzzy Parameters

In this paper, we extend TOPSIS (Technique for Order Preference by Similarity Ideal Solution) for solving Large Scale Multiple Objective Programming problems involving fuzzy parameters. These fuzzy parameters are characterized as fuzzy numbers. For such problems, the ?-Pareto optimality is introduced by extending the ordinary Pareto optimality on the basis of the ?-Level sets of fuzzy numbers. An interactive fuzzy decision making algorithm for generating ?-Pareto optimal solution through TOPSIS approach is provided, where a decision maker (DM) is asked to specify the degree ? and the relative importance of objectives. Finally, a numerical example is given to clarify the main results developed in the paper. <br><br><font color="red"><b> This article has been retracted. Link to the retraction <u><a href="http://dx.doi.org/10.2298/YJOR141008034U">10.2298/YJOR141008034U</a><u></b></font>

scholarly journals Supply Chain Networking Models Under Fuzzy Uncertainty

2022 ◽  
Author(s):  
Abhijit Baidya
Keyword(s):  
Decision Making ◽  
Numerical Integration ◽  
Large Scale ◽  
Fuzzy Numbers ◽  
Real Life ◽  
Mathematical Problems ◽  
Left And Right ◽  
Class Room ◽  
Decision Making Model ◽  
Large Scale Simulations

Abstract In decision-making model, the techniques of numerical analysis have been widely adopted. It is rare for someone to solve a linear program by hand — except perhaps in a class-room. Large-scale simulations would be all but impossible without the aid of a computer. For many people, numerical techniques have superseded analytic techniques as a tool for solving mathematical problems. This paper proposed Generalized LUExponential Trapezoidal Fuzzy Number and their ranking based on numerical integration. In this ranking method, the values are calculated with left and right spreads at some 𝜶 −level of generalized LU-exponential trapezoidal fuzzy numbers and Weddle‘s rule for numerical integration. To illustrate the proposed methods, a fuzzy four dimensional transportation problem (FDTP) is proposed and solved. This ranking approach is very simple and useful for the real life inequality based decision making problems.

Some comments about observations and image processing of comet 29P/Schwassmann-Wachmann 1

1999 ◽  
Vol 173 ◽  
pp. 243-248
Author(s):  
D. Kubáček ◽  
A. Galád ◽  
A. Pravda
Keyword(s):  
Image Processing ◽  
Large Scale ◽  
Harvard College ◽  
Oak Ridge ◽  
Large Scale Structures ◽  
Short Period Comet ◽  
Short Period ◽  
Scale Structures ◽  
Harvard College Observatory ◽  
Period Comet

AbstractUnusual short-period comet 29P/Schwassmann-Wachmann 1 inspired many observers to explain its unpredictable outbursts. In this paper large scale structures and features from the inner part of the coma in time periods around outbursts are studied. CCD images were taken at Whipple Observatory, Mt. Hopkins, in 1989 and at Astronomical Observatory, Modra, from 1995 to 1998. Photographic plates of the comet were taken at Harvard College Observatory, Oak Ridge, from 1974 to 1982. The latter were digitized at first to apply the same techniques of image processing for optimizing the visibility of features in the coma during outbursts. Outbursts and coma structures show various shapes.

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