Loading...

Solving fuzzy quadratic programming problems based on ABS algorithm

Ghanbari, R ; Sharif University of Technology | 2019

495 Viewed
  1. Type of Document: Article
  2. DOI: 10.1007/s00500-019-04013-3
  3. Publisher: Springer Verlag , 2019
  4. Abstract:
  5. 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. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature
  6. Keywords:
  7. ABS algorithm ; Fuzzy quadratic programming problem ; Ranking function ; Information retrieval ; Linear systems ; Quadratic programming ; Coefficient matrix ; Compromised solution ; Fuzzy linear system ; Fuzzy quadratic programming ; Optimization problems ; Quadratic problem ; Quadratic programming problems ; Ranking functions ; Problem solving
  8. Source: Soft Computing ; Volume 23, Issue 22 , 2019 , Pages 11343-11349 ; 14327643 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s00500-019-04013-3