Name
Abstract | ||
|---|---|---|
In this paper a wide class of discrete optimization problems, which can be 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 are 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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.fss.2008.09.001 | Fuzzy Sets and Systems |
Keywords | Field | DocType |
robust solution,fuzzy interval,possibility theory,fuzzy cost,fuzzy scenario,linear programming problem,wide class,finite set,mixed integer linear programming,objective function cost,discrete optimization problem,objective function,minmax,discrete optimization,robust optimization,linear program | Mathematical optimization,Defuzzification,Fuzzy set operations,Robust optimization,Fuzzy transportation,Combinatorial optimization,Fuzzy number,Stochastic programming,Optimization problem,Mathematics | Journal |
Volume | Issue | ISSN |
160 | 5 | Fuzzy Sets and Systems |
Citations | PageRank | References |
18 | 0.71 | 18 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adam Kasperski | 1 | 352 | 33.64 |
| Michał Kulej | 2 | 24 | 1.16 |