Choosing robust solutions in discrete optimization problems with fuzzy costs

被引：27

作者：

Kasperski, Adam ^{[1
]}

Kulej, Michal ^{[1
]}

机构：

[1] Wroclaw Univ Technol, Inst Ind Engn & Management, PL-50370 Wroclaw, Poland

来源：

FUZZY SETS AND SYSTEMS | 2009年 / 160卷 / 05期

关键词：

Discrete optimization; Robust optimization; Fuzzy interval; Possibility theory; Minmax; Minmax regret; LINEAR-PROGRAMMING PROBLEMS; SPANNING TREE PROBLEM; MAX REGRET VERSIONS; INTERVAL DATA; MIN-MAX; COMPLEXITY; APPROXIMATION; ALGORITHM;

D O I：

10.1016/j.fss.2008.09.001

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper it wide class of discrete optimization problems, which can lie formulated as a 0-1 linear programming problem is discussed. It is assumed that the objective function costs are not precisely known. This uncertainty is modeled by specifying a finite set of fuzzy scenarios. Under every fuzzy scenario the costs,ire given as fuzzy intervals. Possibility theory is then applied to chose a solution in such a problem and mixed integer linear programming models are proposed to compute this Solution. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：667 / 682

页数：16

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