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Towards a new strategy for solving fuzzy optimization problems
     
  
  
刊名:
Fuzzy Optimization and Decision Making
作者:
J. M. Cadenas
(Dept. Ingenierfa de la Information y las Comunicaciones, Universidad de Murcia, Murcia, Spain)
J. L. Verdegay
(Dept. Ciencias de la Computation e Inteligencia Artificial, Universidad de Granada, Granada, Spain)
刊号:
519LB020
ISSN:
1568-4539
出版年:
2009
年卷期:
2009, vol.8, no.3
页码:
231-244
总页数:
14
分类号:
O22
关键词:
Fuzzy linear programming
;
Fuzzy optimization
;
Heuristics algorithms
;
Soft computing
;
Data mining
参考中译:
语种:
eng
文摘:
Fuzzy Optimization models and methods has been one of the most and well studied topics inside the broad area of Soft Computing. Particularly relevant is the field of fuzzy linear programming (FLP). Its applications as well as practical realizations can be found in all the real world areas. As FLP problems constitute the basis for solving fuzzy optimization problems, in this paper a basic introduction to the main models and methods in FLP is presented and, as a whole, Linear Programming problems with fuzzy costs, fuzzy constraints and fuzzy coefficients in the technological matrix are analyzed. But fuzzy sets and systems based optimization methods do not end with FLP, and hence in order to solve more complex optimization problems, fuzzy sets based Meta-heuristics are considered, and two main operative approaches described. Provided that these techniques obtain efficient and/or effective solutions, we present a fuzzy rule based methodology for coordinating Meta-heuristics and in addition, to provide intelligence, we propose a process of extraction of the knowledge to conduct the coordination of the system.
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