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Yazar "Tarım, S. Armağan" için İşletme Bölümü Yayın Koleksiyonu listeleme

Yazar "Tarım, S. Armağan" için İşletme Bölümü Yayın Koleksiyonu listeleme

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  • Prestwich, S. D.; Tarım, S. Armağan; Özkan, İbrahim (Springer, 2018-04)
    Probabilistic methods for causal discovery are based on the detection of patterns of correlation between variables. They are based on statistical theory and have revolutionised the study of causality. However, when correlation ...
  • Tunç, Hüseyin; Kılıç, Onur A.; Tarım, S. Armağan; Rossi, Roberto (Inform, 2018-06)
    We present an extended mixed-integer programming formulation of the stochastic lot-sizing problem for the static-dynamic uncertainty strategy. The proposed formulation is significantly more time efficient as compared to ...
  • Pesch, Erwin; Bandalouski, Andrei M.; Kovalyov, Mikhail Y.; Tarım, S. Armağan (EDP Sciences, 2018-03)
    Basic concepts and brief description of revenue management models and decision tools in the hotel business are presented. An overview of the relevant literature on dynamic pricing, forecasting methods and optimization ...
  • Xiang, Mengyuan; Rossi, Roberto; Martin-Barragan, Belen; Tarım, S. Armağan (Elsevier Science Bv, 2018-12-01)
    This paper addresses the single-item single-stocking location non-stationary stochastic lot sizing problem under the (s, S) control policy. We first present a mixed integer non-linear programming (MINLP) formulation for ...
  • Rossi, Roberto; Hnich, Brahim; Tarım, S. Armağan; Prestvvich, Steven (Elsevier Science BV, 2015-11)
    In this work we introduce a novel approach, based on sampling, for finding assignments that are likely to be solutions to stochastic constraint satisfaction problems and constraint optimisation problems. Our approach reduces ...
  • Kılıç, Onur; Tunç, Hüseyin; Tarım, S. Armağan (Elsevier Science Bv, 2018-06-16)
    In this paper, we address the stochastic economic lot sizing problem with remanufacturing under service level constraints. The problem emerges in hybrid production systems where demand can be met via two alternative sources: ...
  • Prestwich, Steven D.; Rossi, Roberto; Tarım, S. Armağan (Springer-Verlag Berlin, 2015)
    Some optimisation problems require a random-looking solution with no apparent patterns, for reasons of fairness, anonymity, undetectability or unpredictability. Randomised search is not a good general approach because ...
  • Visentin, Andrea; Prestwich, Steven; Tarım, S. Armağan (Springer, 2016)
    Principal Components Analysis (PCA) is a data analysis technique widely used in dimensionality reduction. It extracts a small number of orthonormal vectors that explain most of the variation in a dataset, which are called ...