Bicriteria variable selection in a fuzzy regression equation

By considering two criteria of minimum total sum of vagueness and minimum total sum of squares in estimation, this article proposes a variable selection method for a fuzzy regression equation with crisp-input and fuzzy-output. A branch-and-bound algorithm is designed and “the least resistance principle” is adopted to determine the set of compromised solutions. Numerical examples are provided for illustration.