1 Ocak 2018 Dergi makalesi Açık Erişim

Elci, Ozgun; Noyan, Nilay; Bulbul, Kerem

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        "affiliation": "Sabanci Univ, Ind Engn Program, TR-34956 Istanbul, Turkey", 
        "name": "Elci, Ozgun"
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      {
        "affiliation": "Sabanci Univ, Ind Engn Program, TR-34956 Istanbul, Turkey", 
        "name": "Noyan, Nilay"
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        "affiliation": "Sabanci Univ, Ind Engn Program, TR-34956 Istanbul, Turkey", 
        "name": "Bulbul, Kerem"
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    "description": "We focus on optimization models involving individual chance constraints, in which only the right-hand side vector is random with a finite distribution. A recently introduced class of such models treats the reliability levels / risk tolerances associated with the chance constraints as decision variables and trades off the actual cost / return against the cost of the selected reliability levels in the objective function. Leveraging recent methodological advances for modeling and solving chance-constrained linear programs with fixed reliability levels, we develop strong mixed-integer programming formulations for this new variant with variable reliability levels. In addition, we introduce an alternate cost function type associated with the risk tolerances which requires capturing the value-at-risk (VaR) associated with a variable reliability level. We accomplish this task via a new integer linear programming representation of VaR. Our computational study illustrates the effectiveness of our mathematical programming formulations. We also apply the proposed modeling approach to a new stochastic last mile relief network design problem and provide numerical results for a case study based on the real-world data from the 2011 Van earthquake in Turkey. (C) 2018 Elsevier Ltd. All rights reserved.", 
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      "pages": "91-107", 
      "title": "COMPUTERS & OPERATIONS RESEARCH", 
      "volume": "96"
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    "publication_date": "2018-01-01", 
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    "title": "Chance-constrained stochastic programming under variable reliability levels with an application to humanitarian relief network design"
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