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Solving fuzzy quadratic programming problems based on ABS algorithm
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DOI：10.1007/s00500-019-04013-3.png)
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Abstract
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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 programming problem by using ranking function. Also, we study the fuzzy quadratic programming problem with symmetric variables. We show that, in this case, the associate quadratic programming problem is a convex problem, and thus, we able to find the global optimal.
Keywords:
Fuzzy quadratic programming problem
ABS algorithm
Ranking function
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