A Parametric Method to Solve Quadratic Programming Problems with Fuzzy Costs

نویسندگان

  • Ricardo C. Silva
  • Carlos Cruz Corona
  • Akebo Yamakami
چکیده

This work describes a novel fuzzy-sets-based method to solve a particular class of quadratic programming problems which have vagueness coefficients in the objective function. Quadratic programming problems are of utmost importance in an increasing variety of practical fields. In addition, as the ambiguity and vagueness are natural and ever-present in real-life situations requiring solutions, it makes perfect sense to attempt to address them using fuzzy quadratic programming problems. Also, two other methods to solve this kind of problems are briefly described. The proposal uses two phases to solve fuzzy quadratic programming problems. In the first, phase we parametrize the fuzzy problem in several classical alphaproblems with different cutting levels. In the second, phase each of these alpha-problems is solved by using conventional solving techniques. The final fuzzy solution to the problem is obtained by integrating all of these particular alpha-solutions. The results obtained using these two methods are compared with the two-phased proposal outlined above. Keywords— Fuzzy sets, decision making, fuzzy mathematical programming, quadratic optimization.

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تاریخ انتشار 2009