Assortment optimization and pricing under the multinomial logit model with impatient customers: Sequential recommendation and selection
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P. Gao, Y. Ma, N. Chen, G. Gallego, A. Li, P. Rusmevichientong & H. Topaloglu, Operations Research, forthcoming.
Revenue-utility tradeoff in assortment optimization under the multinomial logit model with totally unimodular constraints
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M. Sumida, G. Gallego, P. Rusmevichientong, H. Topaloglu & J. M. Davis, Management Science, forthcoming.
Omnichannel assortment optimization under the multinomial logit model with a features tree
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Venus Lo & Huseyin Topaloglu, M&SOM, forthcoming.
An approximation algorithm for network revenue management under nonstationary arrivals
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Y. Ma, P. Rusmevichientong, M. Sumida & H. Topaloglu, Operations Research, 68, 834-855, 2020.
Assortment optimization under the paired combinatorial logit model
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H. Zhang, P. Rusmevichientong & H. Topaloglu, Operations Research, 68, 741-761, 2020.
Dynamic assortment optimization for reusable products with random usage durations
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P. Rusmevichientong, M. Sumida & H. Topaloglu, Management Science, 66, 2820-2844, 2020.
Assortment optimization under the multinomial logit model with sequential offerings
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N. Liu, Y. Ma & H. Topaloglu, INFORMS Journal on Computing, 32, 835-853, 2020.
Assortment optimization with small consideration sets
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J. Feldman, A. Paul & H. Topaloglu, Operations Research, tech. note, 67, 1283-1299, 2019.
When fixed price meets priority auctions: Competing firms with different pricing and service rules
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J. Gao, K. Iyer & H. Topaloglu, Stochastic Systems, 9, 47-80, 2019.
Pricing problems under the Markov chain choice model
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J. Dong, A.S. Simsek & H. Topaloglu, Production and Operations Management, 28, 157-175, 2019.
An approximation algorithm for capacity allocation over a single flight leg with fare-locking
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M. Sumida & H. Topaloglu, INFORMS Journal on Computing, 31, 83-99, 2019.
Assortment optimization under the multinomial logit model with product synergies
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V. Lo & H. Topaloglu, Operations Research Letters, 47, 546-552, 2019.
Multi-product pricing under the generalized extreme value models with homogeneous price sensitivity parameters
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H. Zhang, P. Rusmevichientong & H. Topaloglu, Operations Research, tech. note, 66, 1559-1570, 2018.
An expectation-maximization algorithm to estimate the parameters of the Markov chain choice model
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A.S. Simsek & H. Topaloglu, Operations Research, tech. note, 66, 748-760, 2018.
Capacitated assortment optimization under the multinomial logit model with nested consideration sets
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J. Feldman & H. Topaloglu, Operations Research, tech. note, 66, 380-391, 2018.
Revenue management under the Markov chain choice model
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J. Feldman & H. Topaloglu, Operations Research, 65, 1322-1342, 2017.
Price competition under linear demand and finite inventories: Contraction and approximate equilibria
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J. Gao, K. Iyer & H. Topaloglu, Operations Research Letters, 45, 382-387, 2017.
Pricing problems under the nested logit model with a quality consistency constraint
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J.M. Davis, H. Topaloglu & D.P. Williamson, INFORMS Journal on Computing, 29, 54-76, 2017.
Delayed purchase options in single-leg revenue management
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N. Aydin, S.I. Birbil & H. Topaloglu, Transportation Science, 51, 1031-1045, 2017.
Bounding optimal expected revenues for assortment optimization under mixtures of multinomial logits
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J. Feldman & H. Topaloglu, Production and Operations Management, 24, 1598-1620, 2015.
Assortment optimization over time
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J.M. Davis, H. Topaloglu & D.P. Williamson, Operations Research Letters, 43, 608-611, 2015.
The d-level nested logit model: Assortment and price optimization problems
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G. Li, P. Rusmevichientong & H. Topaloglu, Operations Research, 63, 325-342, 2015.
Capacity constraints across nests in assortment optimization under the nested logit model
pdffull paper
J. Feldman & H. Topaloglu, Operations Research, tech. note, 63, 812-822, 2015.
Approximation methods for pricing problems under the nested logit model with price bounds
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W.Z. Rayfield, P. Rusmevichientong & H. Topaloglu, INFORMS Journal on Computing, 27, 335-357, 2015.
Constrained assortment optimization for the nested logit model
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G. Gallego & H. Topaloglu, Management Science, 60, 2583-2601, 2014.
A bound on the performance of an optimal ambulance redeployment policy
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M.S. Maxwell, E.C. Ni, C. Tong, S.R. Hunter, S.G. Henderson & H. Topaloglu, Operations Research, 62, 1014-1027, 2014.
Assortment optimization under variants of the nested logit model
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J. Davis, G. Gallego & H. Topaloglu, Operations Research, 62, 250-273, 2014.
Balancing revenues and repair costs under partial information about product reliability
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C. Ding, P. Rusmevichientong & H. Topaloglu, Production and Operations Management, 23, 1899-1918, 2014.
Assortment optimization under the multinomial logit model with random choice parameters
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P. Rusmevichientong, D. Shmoys, C. Tong & H. Topaloglu, Production and Operations Management, 23, 2023-2039, 2014.
Appointment scheduling under patient preference and no-show behavior
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J. Feldman, N. Liu, H. Topaloglu & S. Ziya, Operations Research, 62, 794-811, 2014.
On the approximate linear programming approach for network revenue management problems
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C. Tong & H. Topaloglu, INFORMS Journal on Computing, 26, 131-134, 2014.
Tuning approximate dynamic programming policies for ambulance redeployment via direct search
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M.S. Maxwell, S.G. Henderson & H. Topaloglu, Stochastic Systems, 3, 322-361, 2013.
Dynamic service rate control for a single server queue with Markov modulated arrivals
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R. Kumar, M.E. Lewis & H. Topaloglu, Naval Research Logistics, 60, 661-677, 2013.
Joint stocking and product offer decisions under the multinomial logit model
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H. Topaloglu, Production and Operations Management, 22, 1182-1199, 2013.
Robust assortment optimization in revenue management under the multinomial logit choice model
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P. Rusmevichientong & H. Topaloglu, Operations Research, 60, 865-882, 2012.
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, 46, 460-481, 2012.
Cargo capacity management with allotments and spot market demand
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Y. Levin, M. Nediak & H. Topaloglu, Operations Research, 60, 351-365, 2012.
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, 46, 90-108, 2012.
A duality based approach for network revenue management in airline alliances
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H. Topaloglu, Journal of Revenue and Pricing Management, 11, 500-517, 2012.
Linear programming based decomposition methods for inventory distribution systems
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S. Kunnumkal & H. Topaloglu, European Journal of Operational Research, 211, 282-297, 2011.
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, 10, 455-470, 2011
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.
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, 10, 325-343, 2011.
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, 54, 323-343, 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
Revenue management and pricing analytics
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G. Gallego & H. Topaloglu, Springer, 2019.
Book Chapters
Computation and dynamic programming
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H. Topaloglu, in Wiley Encyclopedia of Operations Research and Management Science, C. Smith, Ed., 2011.
Transportation resource management
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S. Kunnumkal & H. Topaloglu, in Wiley Encyclopedia of Operations Research and Management Science, A. Erera, Ed., 2011.
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
Revenue management under a mixture of multinomial logit and independent demand models
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Y. Cao, P. Rusmevichientong & H. Topaloglu.
Revenue management for boutique hotels: Resources with unit capacities and itineraries over intervals of resources
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Paat Rusmevichientong, Mika Sumida, Huseyin Topaloglu & Yicheng Bai.
Can testing ease social distancing measures? Future evolution of COVID-19 in NYC
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Omar El Housni, Mika Sumida, Paat Rusmevichientong, Huseyin Topaloglu & Serhan Ziya.
Earlier versions of these papers were titled "Assortment planning under the multinomial logit model with totally unimodular constraint structures," "A constant-factor approximation algorithm for network revenue management," and "Assortment optimization with mixtures of logits."