Robust optimization under softness in a fuzzy linear programming problem

Masahiro Inuiguchi

doi:10.1016/S0888-613X(97)10002-0

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Robust optimization under softness in a fuzzy linear programming problem

1998-01-01

Masahiro Inuiguchi *

DOI：10.1016/S0888-613X(97)10002-0

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Abstract

En 中文

In this paper, we discuss the softness and the robustness of the optimality in the setting of linear programming problems with a fuzzy objective function. A fuzzy goal defined on the deviation from the optimal value is introduced, in order to define the soft-optimal solution. Fuzzy coefficients are regarded as possibility distributions. A necessity measure based on the possibility distribution is used for defining a necessarily optimal solution, i.e., a robust-optimal solution. Since a necessarily optimal solution does not exist in many cases, a necessarily soft-optimal solution is defined. A solution algorithm for the best necessarily soft-optimal solution is proposed. (C) 1998 Elsevier Science Inc.

Keywords:

fuzzy linear programming

robustness

soft optimality

necessity

relaxation procedure

bisection method

simplex method

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