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Robust optimization under softness in a fuzzy linear programming problem
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DOI：10.1016/S0888-613X(97)10002-0.png)
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摘要
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.
Keyword:
fuzzy linear programming
robustness
soft optimality
necessity
relaxation procedure
bisection method
simplex method
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