Optimization in science and engineering
Fatemeh Babakordi
Abstract
Since the problems of everyday life are relative , so far various tools such as fuzzy sets, intuitive fuzzy sets, etc. have been expressed to express these ambiguities in mathematical modeling. In 2009, Torra introduced a new horizon for the discussion of hesitant fuzzy sets to discuss issues that are ...
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Since the problems of everyday life are relative , so far various tools such as fuzzy sets, intuitive fuzzy sets, etc. have been expressed to express these ambiguities in mathematical modeling. In 2009, Torra introduced a new horizon for the discussion of hesitant fuzzy sets to discuss issues that are uncertain about decision making. In the course of his work, the quantitative and qualitative expansion of uncertain fuzzy sets is discussed. In this article, for the purpose of introducing more researchers to hesitant fuzzy sets, we review the types of hesitant fuzzy sets such as dual uncertain fuzzy sets, generalized hesitant fuzzy sets, and so on.
Fuzzy Optimization
Nemat Allah Taghi-Nezhad; Fatemeh babakordi
Abstract
Quadratic programming problem is one of the important problem of classic optimization problems that the aim is to find the maximum or minimum amount of a quadratic function under linear constraints. In this paper, the quadratic programming problem where its parameters are all nonnegative fuzzy numbers ...
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Quadratic programming problem is one of the important problem of classic optimization problems that the aim is to find the maximum or minimum amount of a quadratic function under linear constraints. In this paper, the quadratic programming problem where its parameters are all nonnegative fuzzy numbers is discussed and a new algorithm based on fuzzy operations and fuzzy arithmetic is presented where reduced the fuzzy model into three smaller and more simple crisp problem. Then, by solving these crisp models using conventional algorithms such as SQP and by combining these solutions, the optimal solution of the fuzzy problem is obtained. Finally, an example is solved to implement the proposed algorithm and show the applicability of it.