Multiple objective linear programming models with interval coefficients – an illustrated overview

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 coefficie...

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Bibliographic Details
Published in:European journal of operational research Vol. 181; no. 3; pp. 1434 - 1463
Main Authors: Oliveira, Carla, Antunes, Carlos Henggeler
Format: Journal Article Conference Proceeding
Language:English
Published: Amsterdam Elsevier B.V 16.09.2007
Elsevier
Elsevier Sequoia S.A
Series:European Journal of Operational Research
Subjects:
ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary: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.
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2005.12.042