Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
481928 | European Journal of Operational Research | 2007 | 30 Pages |
Abstract
In most real-world situations, the coefficients of decision support models are not exactly known. In this context, it is convenient to consider an extension of traditional mathematical programming models incorporating their intrinsic uncertainty, without assuming the exactness of the model coefficients. Interval programming is one of the tools to tackle uncertainty in mathematical programming models. Moreover, most real-world problems inherently impose the need to consider multiple, conflicting and incommensurate objective functions. This paper provides an illustrated overview of the state of the art of Interval Programming in the context of multiple objective linear programming models.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Carla Oliveira, Carlos Henggeler Antunes,