On Solving a class of stochastic multiobjective integer linear programming problems with Interactive Based Approach

Decision problems of stochastic or probabilistic optimization arise when certain coefficient of an optimization model are not fixed or known but are instead, to some extent, stochastic(or random or probabilistic) quantities. This paper focused on multiobjective stochastic optimization. We propose a...

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Veröffentlicht in:Journal of physics. Conference series Jg. 1255; H. 1; S. 12088 - 12094
Hauptverfasser: Suparni, Mawengkang, Herman, Sitompul, Opim Salim, Suwilo, Saib
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bristol IOP Publishing 01.08.2019
Schlagworte:
Integer programming
Linear programming
Multiple objective analysis
Optimization
Probability theory
Random variables
Randomness
ISSN:1742-6588, 1742-6596
Online-Zugang:Volltext
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Zusammenfassung:Decision problems of stochastic or probabilistic optimization arise when certain coefficient of an optimization model are not fixed or known but are instead, to some extent, stochastic(or random or probabilistic) quantities. This paper focused on multiobjective stochastic optimization. We propose a method for solving a multiobjective chance constraints integer programming problem based on interactive approach. We assume that there is randomness in the right-hand sides of the constraints only and that the random variables are normally distributed. Some examples are presented.
Bibliographie:ObjectType-Article-1
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ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1255/1/012088