Browsing by Subject "robust optimization"

Now showing 1 - 3 of 3

Open Access
A critical review of the approaches to optimization problems under uncertainty
(2001) Gürtuna, Filiz
In this study, the issue of uncertainty in optimization problems is studied. First of all, the meaning and sources of uncertainty are explained and then possible ways of its representation are analyzed. About the modelling process, different approaches as sensitivity analysis, parametric programming, robust optimization, stochastic programming, fuzzy programming, multiobjective programming and imprecise optimization are presented with advantages and disadvantages from different perspectives. Some extensions of the concepts of imprecise optimization are also presented.
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Robust auction design under multiple priors
(2015) Koçyiğit, Çağıl
In optimal auction design literature, it is a common assumption that valuations of buyers are independently drawn from a unique distribution. In this thesis, we study auctions with ambiguity for an environment where valuation distribution is uncertain itself and introduce a linear programming approach to robust auction design problem. We develop an algorithm that gives the optimal solution to the problem under certain assumptions when the seller is ambiguity averse with prior set P and the buyers are ambiguity neutral with a prior f ∈ P. Also, we consider the case where the buyers are ambiguity averse as the seller and formulate this problem as a mixed integer programming problem. Then, we propose a hybrid algorithm that enables to achieve a good solution for this problem in a reduced time.
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Robust solutions to single and multi-period machine layout problems with interval flows
(1997) Tüfekçi, Özgür Atilla
Design clecisous are genevcUly given in the early stages when there is a great deal of inexactness in the data gathered. In this study, we consider the plant Uiyout problem witli inexactness in material flow quantities with the aim of designing robust layouts. Material flow quantities are assumed to lie in a priori specified intervals based, for example, on low ¿md high demands. The robustness criterion we use is to minimize the maximum I’egret. We extend our work to the multi-period case where a distinction is made between reversible and irreversible layout decisions.