Comparison of fuzzy, stochastic and deterministic methods in linear programming

被引：0
|
作者：
Lodwick, Weldon [1 ]
Jamison, Dave [1 ]
Russell, Steve [1 ]
机构：
[1] Univ of Colorado at Denver, Denver, United States
来源：
Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS | 2000年
关键词：
Fuzzy sets - Mathematical models - Optimization - Random processes;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Relationships among some fuzzy, stochastic, and deterministic optimization methods were used for solving linear programming problems. Fuzzy linear programs (FLP) can be formed depending on the fuzzification of the parameters and the inequalities, where the deterministic case is a degenerate fuzzy interval. Fuzzification of the inequality and the resulting FLP is called flexible fuzzy programming. Ambiguity arises when the coefficients are fuzzified and is called the modality fuzzy optimization.
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页码：321 / 325
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