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Guzin Bayraksan - Publications

Affiliations: 
Applied Mathematics University of Arizona, Tucson, AZ 
Area:
Operations Research, Applied Mathematics
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25 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2019 Rahimian H, Bayraksan G, Homem-de-Mello T. Controlling risk and demand ambiguity in newsvendor models European Journal of Operational Research. 279: 854-868. DOI: 10.1016/J.Ejor.2019.06.036  0.454
2019 Rahimian H, Bayraksan G, Homem-de-Mello T. Identifying effective scenarios in distributionally robust stochastic programs with total variation distance Mathematical Programming. 173: 393-430. DOI: 10.1007/S10107-017-1224-6  0.463
2018 Bayraksan G. An improved averaged two-replication procedure with Latin hypercube sampling Operations Research Letters. 46: 173-178. DOI: 10.1016/J.Orl.2017.12.005  0.456
2016 Zhang W, Rahimian H, Bayraksan G. Decomposition Algorithms for Risk-Averse Multistage Stochastic Programs with Application to Water Allocation under Uncertainty Informs Journal On Computing. 28: 385-404. DOI: 10.1287/Ijoc.2015.0684  0.585
2016 Stockbridge R, Bayraksan G. Variance reduction in Monte Carlo sampling-based optimality gap estimators for two-stage stochastic linear programming Computational Optimization and Applications. 64: 407-431. DOI: 10.1007/S10589-015-9814-9  0.735
2015 Love D, Bayraksan G. Overlapping batches for the assessment of solution quality in stochastic programs Acm Transactions On Modeling and Computer Simulation. 25. DOI: 10.1145/2701421  0.53
2015 Lan F, Bayraksan G, Lansey K. Reformulation linearization technique based branch-and-reduce approach applied to regional water supply system planning Engineering Optimization. DOI: 10.1080/0305215X.2015.1016508  0.437
2015 Homem-De-Mello T, Bayraksan G. Stochastic constraints and variance reduction techniques International Series in Operations Research and Management Science. 216: 245-276. DOI: 10.1007/978-1-4939-1384-8_9  0.383
2014 Homem-de-Mello T, Bayraksan G. Monte Carlo sampling-based methods for stochastic optimization Surveys in Operations Research and Management Science. 19: 56-85. DOI: 10.1016/J.Sorms.2014.05.001  0.518
2014 Kucuksari S, Khaleghi AM, Hamidi M, Zhang Y, Szidarovszky F, Bayraksan G, Son YJ. An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments Applied Energy. 113: 1601-1613. DOI: 10.1016/J.Apenergy.2013.09.002  0.361
2013 Love D, Bayraksan G. Two-stage likelihood robust linear program with application to water allocation under uncertainty Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, Wsc 2013. 77-88. DOI: 10.1109/WSC.2013.6721409  0.45
2013 Zhang W, Chung G, Pierre-Louis P, Bayraksan G, Lansey K. Reclaimed water distribution network design under temporal and spatial growth and demand uncertainties Environmental Modelling and Software. 49: 103-117. DOI: 10.1016/J.Envsoft.2013.07.008  0.645
2013 Stockbridge R, Bayraksan G. A probability metrics approach for reducing the bias of optimality gap estimators in two-stage stochastic linear programming Mathematical Programming. 142: 107-131. DOI: 10.1007/S10107-012-0563-6  0.745
2013 Love D, Bayraksan G. A likelihood robust method for water allocation under uncertainty Iie Annual Conference and Expo 2013. 3633-3642.  0.404
2012 Keller B, Bayraksan G. Case---Quantifying Operational Risk in Financial Institutions Informs Transactions On Education. 12: 106-113. DOI: 10.1287/Ited.1110.0075Cs  0.59
2012 Keller B, Bayraksan G. Case Article---Quantifying Operational Risk in Financial Institutions Informs Transactions On Education. 12: 100-105. DOI: 10.1287/Ited.1110.0075Ca  0.627
2012 Keller B, Bayraksan G. Disjunctive decomposition for two-stage stochastic mixed-binary programs with generalized upper bound constraints Informs Journal On Computing. 24: 172-186. DOI: 10.1287/Ijoc.1100.0442  0.682
2012 Bayraksan G, Pierre-Louis P. Fixed-width sequential stopping rules for a class of stochastic programs Siam Journal On Optimization. 22: 1518-1548. DOI: 10.1137/090773143  0.703
2012 Zhang W, Bayraksan G, Chung G, Lansey K. Optimal reclaimed water network design via two-stage stochastic binary programming Water Distribution Systems Analysis 2010 - Proceedings of the 12th International Conference, Wdsa 2010. 843-860. DOI: 10.1061/41203(425)78  0.368
2011 Bayraksan G, Morton DP. A sequential sampling procedure for stochastic programming Operations Research. 59: 898-913. DOI: 10.1287/Opre.1110.0926  0.532
2011 Pierre-Louis P, Bayraksan G, Morton DP. A combined deterministic and sampling-based sequential bounding method for stochastic programming Proceedings - Winter Simulation Conference. 4167-4178. DOI: 10.1109/WSC.2011.6148105  0.71
2010 Keller B, Bayraksan G. Scheduling jobs sharing multiple resources under uncertainty: A stochastic programming approach Iie Transactions (Institute of Industrial Engineers). 42: 16-30. DOI: 10.1080/07408170902942683  0.72
2009 Chung G, Lansey K, Bayraksan G. Reliable water supply system design under uncertainty Environmental Modelling and Software. 24: 449-462. DOI: 10.1016/J.Envsoft.2008.08.007  0.426
2007 Bayraksan G, Morton DP. Sequential sampling for solving stochastic programs Proceedings - Winter Simulation Conference. 421-429. DOI: 10.1109/WSC.2007.4419631  0.441
2006 Bayraksan G, Morton DP. Assessing solution quality in stochastic programs Mathematical Programming. 108: 495-514. DOI: 10.1007/S10107-006-0720-X  0.524
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