Robust assortment optimization in revenue management under the multinomial logit choice model
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P. Rusmevichientong & H. Topaloglu, Operations Research, forthcoming.
A duality based approach for network revenue management in airline alliances
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H. Topaloglu, Journal of Revenue and Pricing Management, forthcoming.
Tractable open loop policies for joint overbooking and capacity control over a single flight leg with multiple fare classes
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H. Topaloglu, I. Birbil, J.B.G. Frenk & N. Noyan,Transportation Science, forthcoming.
Cargo capacity management with allotments and spot market demand
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Y. Levin, M. Nediak & H. Topaloglu, Operations Research, forthcoming.
A randomized linear programming method for network revenue management with product-specific no-shows
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S. Kunnumkal, K. Talluri & H. Topaloglu, Transportation Science, forthcoming.
A stochastic approximation algorithm to compute bid prices for joint capacity allocation and overbooking over an airline network
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S. Kunnumkal & H. Topaloglu, Naval Research Logistics, forthcoming.
Linear programming based decomposition methods for inventory distribution systems
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S. Kunnumkal & H. Topaloglu, European Journal of Operational Research, forthcoming.
A randomized linear program for the network revenue management problem with customer choice behavior
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S. Kunnumkal & H. Topaloglu, Journal of Revenue and Pricing Management, forthcoming.
Using decomposition methods to solve pricing problems in network revenue management
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A. Erdelyi & H. Topaloglu, Journal of Revenue and Pricing Management, forthcoming.
Approximate dynamic programming for dynamic capacity allocation with multiple priority levels
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A. Erdelyi & H. Topaloglu, IIE Transactions, 43, 129-142, 2011.
A stochastic approximation algorithm for making pricing decisions in network revenue management problems
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S. Kunnumkal & H. Topaloglu, Journal of Revenue and Pricing Management, 9, 419-422, 2010.
A new dynamic programming decomposition method for the network revenue management problem with customer choice behavior
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S. Kunnumkal & H. Topaloglu, Production and Operations Management, 19, 575-590, 2010.
A stochastic approximation method with max-norm projections and its applications to the Q-Learning algorithm
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S. Kunnumkal & H. Topaloglu, The ACM Transactions on Modeling and Computer Simulation, 20, 12:1-12:26, 2010.
A dynamic programming decomposition method for making overbooking decisions over an airline network
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A. Erdelyi & H. Topaloglu, INFORMS Journal on Computing, 22, 443-456, 2010.
Computing time-dependent bid-prices in network revenue management problems
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H. Topaloglu & S. Kunnumkal, Transportation Science, 44, 38-62, 2010.
Approximate dynamic programming for ambulance redeployment
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M.S. Maxwell, M. Restrepo, S.G. Henderson & H. Topaloglu, INFORMS Journal on Computing, 22, 266-281, 2010.
A stochastic approximation method for the single-leg revenue management problem with discrete demand distributions
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S. Kunnumkal & H. Topaloglu, Mathematical Methods of Operations Research, 70, 477-504, 2009. (The original publication is available at www.springerlink.com.)
Using Lagrangian relaxation to compute capacity-dependent bid prices in network revenue management
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H. Topaloglu, Operations Research, 57, 637-649, 2009.
A tighter variant of Jensen's lower bound for stochastic programs and separable approximations to recourse functions
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H. Topaloglu, European Journal of Operational Research, 199, 315-322, 2009.
Erlang loss models for the static deployment of ambulances
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M. Restrepo, S.G. Henderson & H. Topaloglu, Health Care Management Science, 12, 67-79, 2009.
Computing protection level policies for dynamic capacity allocation problems by using stochastic approximation methods
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A. Erdelyi & H. Topaloglu, IIE Transactions, 41, 498-510, 2009.
On the asymptotic optimality of the randomized linear program for network revenue management
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H. Topaloglu, European Journal of Operational Research, Special Issue on Pricing and Revenue Management, 197, 884-896, 2009.
Separable approximations for joint capacity control and overbooking decisions in network revenue management
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A. Erdelyi & H. Topaloglu, Journal of Revenue and Pricing Management, 8, 3-20, 2009.
A tractable revenue management model for capacity allocation and overbooking over an airline network
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S. Kunnumkal & H. Topaloglu, Flexible Services and Manufacturing Journal, 20, 125-147, 2008.
A duality-based relaxation and decomposition approach for inventory distribution systems
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S. Kunnumkal & H. Topaloglu, Naval Research Logistics, 55, 612-631, 2008.
A refined deterministic linear program for the network revenue management problem with customer choice behavior
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S. Kunnumkal & H. Topaloglu, Naval Research Logistics, 55, 563-580, 2008.
A stochastic approximation method to compute bid prices in network revenue management problems
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H. Topaloglu, INFORMS Journal on Computing, 20, 596-610, 2008.
Using stochastic approximation methods to compute optimal base-stock levels in inventory inventory control problems
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S. Kunnumkal & H. Topaloglu, Operations Research, 56, 646-664, 2008.
Exploiting the structural properties of the underlying Markov decision problem in Q-learning algorithm
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S. Kunnumkal & H. Topaloglu, INFORMS Journal on Computing, 20, 288-301, 2008.
Price discounts in exchange for reduced customer demand variability and applications to advance demand information acquisition
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S. Kunnumkal & H. Topaloglu, International Journal of Production Economics, 111, 543-561, 2008.
Incorporating pricing decisions into the stochastic dynamic fleet management problem
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H. Topaloglu & W.B. Powell, Transportation Science, 41, 281-301, 2007.
Incorporating the pricing decisions into dynamic fleet management models
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G.J. King & H. Topaloglu, Journal of the Operational Research Society, 58, 1064-1074, 2007.
Sensitivity analysis of a dynamic fleet management model using approximate dynamic programming
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H. Topaloglu & W.B. Powell, Operations Research, 55, 319-331, 2007.
Approximate dynamic programming methods for an inventory allocation problem under uncertainty
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H. Topaloglu & S. Kunnumkal, Naval Research Logistics, 53, 822-841, 2006.
A parallelizable dynamic fleet management model with random travel times
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H. Topaloglu, European Journal of Operational Research, 175, 782-805, 2006.
Dynamic programming approximations for stochastic, time-staged integer multicommodity flow problems
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H. Topaloglu & W.B. Powell, INFORMS Journal on Computing, 18, 31-42, 2006.
An approximate dynamic programming approach for a product distribution problem
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H. Topaloglu, IIE Transactions, 37, 697-710, 2005.
A distributed decision making structure for dynamic resource allocation using nonlinear functional approximations
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H. Topaloglu & W.B. Powell, Operations Research, 53, 281-297, 2005.
Learning algorithms for separable approximations of discrete stochastic optimization problems
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W.B. Powell, A. Ruszczynski & H. Topaloglu, Mathematics of Operations Research, 29, 814-836, 2004.
An algorithm for approximating piecewise linear concave functions from sample gradients
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H. Topaloglu & W.B. Powell, Operations Research Letters, 31, 66-76, 2003.
Book Chapters
Computation and dynamic programming
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H. Topaloglu, in Wiley Encyclopedia of Operations Research and Management Science, C. Smith, Ed., forthcoming.
Transportation resource management
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S. Kunnumkal & H. Topaloglu, in Wiley Encyclopedia of Operations Research and Management Science, A. Erera, Ed., forthcoming.
A parallelizable and approximate dynamic programming-based dynamic fleet management model with random travel times and multiple vehicle types
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H. Topaloglu, in Dynamic Fleet Management: Concepts, Systems, Algorithms and Case Studies, V.S. Zeimpekis, G.M. Giaglis, C.D. Tarantilis & I. Minis, eds., 2007.
Approximate dynamic programming for large-scale resource allocation problems
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W.B. Powell & H. Topaloglu, in TutORials in Operations Research, M.P. Johnson, B. Norman & N. Secomandi, eds., 2006.
Fleet management
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W.B. Powell & H. Topaloglu, in Applications of Stochastic Programming, Math Programming Society – SIAM Series in Optimization, S. Wallace & W. Ziemba, eds., 2005.
Stochastic programming in transportation and logistics
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W.B. Powell & H. Topaloglu, in Handbooks in Operations Research and Management Science, volume on Stochastic Programming, A. Shapiro & A. Ruszczynski, eds., 2003.
Work-in-Progress
Assortment optimization with mixtures of logits
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P. Rusmevichientong, D. Shmoys & H. Topaloglu.
Joint stocking and product offer decisions under the multinomial logit model
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H. Topaloglu.
Tuning approximate dynamic programming policies for ambulance redeployment via direct search
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M.S. Maxwell, S.G. Henderson & H. Topaloglu.
Balancing revenues and repair costs under partial information about product reliability
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C. Ding, P. Rusmevichientong & H. Topaloglu.
On approximate linear programming approach for network revenue management problems
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C. Tong & H. Topaloglu.
Assortment optimization under variants of the nested logit model
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J. Davis, G. Gallego & H. Topaloglu.