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Duality in bipolar triangular fuzzy number quadratic programming problems
, Article Proceedings of the International Conference on Intelligent Sustainable Systems, ICISS 2017, 7 December 2017 through 8 December 2017 ; 19 June , 2018 , Pages 1236-1238 ; 9781538619599 (ISBN) ; Ghanbari, R ; Mahdavi Amiri, N ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2018
Abstract
We discuss how to solve bipolar fuzzy quadratic programming problems, where the parameters are bipolar triangular fuzzy numbers, making use of linear ranking functions. Also, we explore some duality properties of bipolar triangular fuzzy number quadratic programming problem (BTFNQPP). © 2017 IEEE
A variables neighborhood search algorithm for solving fuzzy quadratic programming problems using modified Kerre’s method
, Article Soft Computing ; Volume 23, Issue 23 , 2019 , Pages 12305-12315 ; 14327643 (ISSN) ; Ghorbani Moghadam, K ; Mahdavi Amiri, N ; Sharif University of Technology
Springer Verlag
2019
Abstract
To solve a fuzzy optimization problem, we need to compare fuzzy numbers. Here, we make use of our recently proposed modified Kerre’s method as an effective approach for comparison of LR fuzzy numbers. Using our new results on LR fuzzy numbers, we show that to compare two LR fuzzy numbers, we do not need to compute the fuzzy maximum of two numbers directly. We propose a new variable neighborhood search approach for solving fuzzy number quadratic programming problems by using the modified Kerre’s method. In our algorithm, a local search is performed using descent directions, found by solving five crisp mathematical programming problems. In several available methods, a fuzzy optimization...
Solving fuzzy quadratic programming problems based on ABS algorithm
, Article Soft Computing ; Volume 23, Issue 22 , 2019 , Pages 11343-11349 ; 14327643 (ISSN) ; Ghorbani Moghadam, K ; Sharif University of Technology
Springer Verlag
2019
Abstract
Recently, Ghanbari and Mahdavi-Amiri (Appl Math Model 34:3363–3375, 2010) gave the general compromised solution of an LR fuzzy linear system using ABS algorithm. Here, using this general solution, we solve quadratic programming problems with fuzzy LR variables. We convert fuzzy quadratic programming problem to a crisp quadratic problem by using general solution of fuzzy linear system. By using this method, the crisp optimization problem has fewer variables in comparison with other methods, specially when rank of the coefficient matrix is full. Thus, solving the fuzzy quadratic programming problem by using our proposed method is computationally easier than the solving fuzzy quadratic...