Solution approaches for the multiobjective stochastic programming

We survey in this paper various solution approaches for multiobjective stochastic problems where random variables can be in both objectives and constraints parameters. Once a problem requires a stochastic formulation, a first step consists in transforming the problem into its deterministic formulati...

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Bibliographic Details
Published in:European journal of operational research Vol. 216; no. 1; pp. 1 - 16
Main Author: Abdelaziz, Fouad Ben
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 2012
Elsevier
Elsevier Sequoia S.A
Subjects:
Applied sciences
Classification
Computational efficiency
Computing time
Decision theory. Utility theory
Efficient solutions
Exact sciences and technology
Mathematical models
Mathematical problems
Mathematical programming
Multiobjective stochastic programming
Operational research
Operational research and scientific management
Operational research. Management science
Programming
Random variables
Stochastic goal programming
Stochastic models
Stochasticity
Studies
Transformations
Stochastic goal programming
Multiobjective stochastic programming
Efficient solutions
Stochastic model
Efficiency
Multiobjective programming
Random variable
Goal programming
Stochastic programming
ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary:We survey in this paper various solution approaches for multiobjective stochastic problems where random variables can be in both objectives and constraints parameters. Once a problem requires a stochastic formulation, a first step consists in transforming the problem into its deterministic formulation. We propose to classify and evaluate such transformations with regards to the many proposed concepts of efficiency. The paper addresses also some applications of the multiobjective stochastic programming models.
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2011.03.033