Systems & Industrial Engineering  _:_  Güzin Bayraksan  _:_  The University of Arizona  

 

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Publications

 

 
 

Keller, B.D. and G. Bayraksan, “Multiple Resource Constrained Job Scheduling under Uncertainty: A Stochastic Programming Approach,” under review. (paper [pdf])

Bayraksan, G. and D. P. Morton, “A Sequential Sampling Procedure for Stochastic Programming,” conditionally accepted to Operations Research(paper [pdf])

Bayraksan, G. and D. P. Morton, “Assessing Solution Quality in Stochastic Programs,” Mathematical Programming, 108: 495-514, 2006. (preprint [pdf])

Chung, G., K. Lansey and G. Bayraksan, “Reliable Water Supply System Design under Uncertainty,” conditionally accepted to Journal of Environmental Modelling and Software.

Bayraksan, G., D. P. Morton and A. Partani “Simulation-Based Optimality Tests for Stochastic Programs,” Planning Under Uncertainty: Stochastic Programming, G. Infanger and G. B. Dantzig (eds), Kluwer Series on Advances in Mathematical Programming, forthcoming. (paper [pdf])

Bayraksan, G. and D.P. Morton, “Sequential Sampling for Solving Stochastic Programs,”  Proceedings of the 2007 Winter Simulation Conference, 2007.

Bayraksan, G. and D. P. Morton, “Testing Solution Quality in Stochastic Programming: A Single Replication Procedure,” Proceedings of the 16th Symposium of IASC on Computational Statistics, Physica-Verlag/Springer, Prague, Czech Republic, 2004.  (paper [pdf])

Ongoing Projects:

Monte Carlo simulation-based methods for Stochastic Programming:

*  Fixed-Width Sequential Stopping Rules for A Class of Stochastic Programs (abstract)

*  A Sampling-Based Sequential Approximation Method (abstract)

*  A Probability Metrics Approach for Bias and Variance Reduction in Optimality Gap Estimation (abstract)

Modeling and Optimization of Complex Stochastic Systems:

*  Multiple Resource Constrained Job Scheduling under Uncertainty

*  Water Reuse System with two-stage Stochastic Integer Programming

 

 

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