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Elci, Ozgun; Noyan, Nilay; Bulbul, Kerem
{
"DOI": "10.1016/j.cor.2018.03.011",
"abstract": "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.",
"author": [
{
"family": "Elci",
"given": " Ozgun"
},
{
"family": "Noyan",
"given": " Nilay"
},
{
"family": "Bulbul",
"given": " Kerem"
}
],
"container_title": "COMPUTERS & OPERATIONS RESEARCH",
"id": "35421",
"issued": {
"date-parts": [
[
2018,
1,
1
]
]
},
"page": "91-107",
"title": "Chance-constrained stochastic programming under variable reliability levels with an application to humanitarian relief network design",
"type": "article-journal",
"volume": "96"
}
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