Real-time optimization of personalized assortments

Management Science

Volumn 60, Issue 6, 2014, Pages 1532-1551

  Golrezaei, Negin ^a   Nazerzadeh, Hamid ^a   Rusmevichientong, Paat ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Assortment optimization; Choice models; Online algorithms; Personalization

Indexed keywords

ALGORITHMS; ELECTRONIC COMMERCE; SUPPLY CHAINS;

ASSORTMENT OPTIMIZATION; CHOICE MODEL; HYBRID ALGORITHMS; ON-LINE ALGORITHMS; OPTIMAL COMPETITIVE RATIOS; PERSONALIZATIONS; REAL-TIME OPTIMIZATION; WORST-CASE PERFORMANCE;

SALES;

EID: 84902249009     PISSN: 00251909     EISSN: 15265501     Source Type: Journal    
DOI: 10.1287/mnsc.2014.1939     Document Type: Article

References (50)

1. Acimovic J, Graves S (2012) Making better fulfillment decisions on the fly in an online retail environment. Working paper, Massachusetts Institute of Technology, Cambridge.
2. Agrawal S, Wang Z, Ye Y (2009) A dynamic near-optimal algorithm for online linear programming. Working paper, Stanford University, Stanford, CA.
3. Amazon's Recommendation Systems (2012) Improve your recommendations. Accessed August 15, 2012, http://www.amazon. com/gp/help/customer/display.html/ ref=pd-ys-help-iyr ?ie=UTF8&nodeId=13316081.
4. Azar Y, Birnbaum BE, Karlin AR, Nguyen CT (2009) On revenue maximization in second-price ad auctions. Fiat A, Sanders P, eds. Algorithms-ESA 2009, Lecture Notes in Computer Science, Vol. 5757 (Springer, Berlin), 155-166.
5. Ball MO, Queyranne M (2009) Toward robust revenue management: Competitive analysis of online booking. Oper. Res. 57(4):950-963.
6. Bernstein F, Kök AG, Xie L (2011) Dynamic assortment customization with limited inventories. Working paper, Duke University, Durham, NC.
7. Besbes O, Sauré D (2012) Dynamic pricing strategies in the presence of demand shocks. Working paper, Columbia University, New York.
8. Besbes O, Zeevi A (2011) On the minimax complexity of pricing in a changing environment. Oper. Res. 59(1):66-79.
9. Bhat CR (2002) Recent methodological advances relevant to activity and travel behavior analysis. Mahmassani HS, ed. In Perpetual Motion: Travel Behavior Research Opportunities and Application Challenges (Emerald Group Publishing, Bingley, UK), 381-414.
10. Buchbinder N, Naor J (2007) The design of competitive online algorithms via a primal-dual approach. Foundations and Trends Theoret. Comput. Sci. 3(2-3):93-263.
11. Buchbinder N, Jain K, Naor J (2007) Online primal-dual algorithms for maximizing ad-auctions revenue. Arge L, Hoffmann M, Welzl E, eds. Algorithms-ESA 2007, Lecture Notes in Computer Science, Vol. 4698 (Springer, Berlin), 253-264.
12. Chan CW, Farias VF (2009) Stochastic depletion problems: Effective myopic policies for a class of dynamic optimization problems. Math. Oper. Res. 34(2):333-350.
13. Chen Y, Farias VF (2013) Simple policies for dynamic pricing with imperfect forecasts. Oper. Res. 61(3):612-624.
14. Ciocan DF, Farias V (2012) Model predictive control for dynamic resources allocation. Math. Oper. Res. 37(3):501-525.
15. Clifford S (2012) Shopper alert: Price may drop for you alone. New York Times (August 9), http://www.nytimes.com/2012/08/10/business/supermarkets-try- customizing-prices-for-shoppers.html?pagewanted=all.
16. Davis J, Gallego G, Topaloglu H (2014) Assortment optimization under variants of the nested logit model. Oper. Res. 62(2):250-273.
17. Devenur NR, Hayes TP (2009) The AdWords problem: online keyword matching with budgeted bidders under random permutations. Chuang J, Fortnow L, Pu P, eds. EC'09: Proc. 10th ACM Conf. Electronic Commerce (ACM, New York), 71-78.
18. Farias VF, Jagabathula S, Shah D (2013) A nonparametric approach to modeling choice with limited data. Management Sci. 59(2):305-322.
19. Feldman J, Henzinger M, Korula N, Mirrokni V, Stein C (2010) Online stochastic packing applied to display ad allocation. de Berg M, Meyer U, eds. Algorithms-ESA 2010, Lecture Notes in Computer Science, Vol. 6346 (Springer, Berlin), 182-194.
20. Gallego G, Topaloglu H (2014) Constrained assortment optimization for the nested logit model. Management Sci. Forthcoming.
21. Gallego G, van Ryzin G (1994) On the relationship between inventory costs and variety benefits in retail assortments. Management Sci. 40(8):999-1020.
22. Gallego G, Iyengar G, Phillips R, Dubey A (2004) Managing flexible products on a network. Working paper, Columbia University, New York.
23. Gaur V, Honhon D (2006) Assortment planning and inventory decisions under a locational choice model. Management Sci. 52(10):1528-1543.
24. Goel A, Mahdian M, Nazerzadeh H, Saberi A (2010) Advertisement allocation for generalized second-pricing schemes. Oper. Res. Lett. 38(6):571-576.
25. Goyal V, Levi R, Segev D (2011) Near-optimal algorithms for the assortment planning problem under dynamic substitution and stochastic demand. Working paper, Columbia University, New York.
26. Helft M, Vega T (2010) Retargeting ads follow surfers to other sites. New York Times (August 29), http://www.nytimes.com/2010/08/30/technology/30adstalk. html.
27. Honhon D, Gaur V, Seshadri S (2010) Assortment planning and inventory decisions under stockout based substitution. Oper. Res. 58(5):1364-1379.
28. Jaillet P, Lu X (2012) Near-optimal online algorithms for dynamic resource allocations. Working paper, Massachusetts Institute of Technology, Cambridge.
29. Jasin S, Kumar S (2012) A re-solving heuristic with bounded revenue loss for network revenue management with customer choice. Math. Oper. Res. 37(2):313-345.
30. Kalyanasundaram B, Pruhs K (2000) An optimal deterministic algorithm for online b-matching. Theorictal Comput. Sci. 233(1-2):319-325.
31. Kök AG, Fisher M, Vaidyanathan R (2008) Assortment planning: Review of literature and industry practice. Retail Supply Chain Management 122(1):99-153.
32. Li G, Rusmevichientong P, Topaloglu H (2013) The d-level nested logit model: Assortment and price optimization problems. Working paper, Marshall School of Business, University of Southern California, Los Angeles.
33. Liu Q, van Ryzin GJ (2008) On the choice-based linear programming model for network revenue management. Manufacturing Service Oper. Management 10(2):288-310.
34. Mahajan S, van Ryzin GJ (2001) Stocking retail assortments under dynamic consumer substitution. Oper. Res. 49(3):334-351.
35. Mahdian M, Nazerzadeh H, Saberi A (2007) Allocating online advertisement space with unreliable estimates. MacKie-Mason JK, Parkes DC, Resnick P, eds. Proc. 8th ACM Conf. Electronic Commerce (ACM, New York), 288-294.
36. Mahdian M, Nazerzadeh H, Saberi A (2012) Online optimization with uncertain information. ACM Trans. Algorithms 8(1):1-29.
37. Mattioli D (2012) On Orbitz, Mac users steered to pricier hotels. Wall Street Journal (August 23), http://online.wsj.com/news/articles/ SB10001424052702304458604577488822667325882.
38. Mehta A, Saberi A, Vazirani UV, Vazirani VV (2007) AdWords and generalized online matching. J. ACM 54(5): Article 22.
39. Mirrokni VS, Gharan SO, Zadimoghaddam M (2012) Simultaneous approximations for adversarial and stochastic online budgeted allocation. Rabani Y, ed. Proc. Twenty-Third Annual ACM-SIAM Sympos. Discrete Algorithms (SIAM, Philadelphia), 1690-1701.
40. Rusmevichientong P, Shen Z-JM, Shmoys DB (2009) A PTAS for capacitated sum-of-ratios optimization. Oper. Res. Lett. 37(4):230-238.
41. Rusmevichientong P, Shen Z-JM, Shmoys DB (2010) Dynamic assortment optimization with a multinomial logit choice model and capacity constraint. Oper. Res. 58(6):1666-1680.
42. Smith SA, Agrawal N (2000) Management of multi-item retail inventories systems with demand substitution. Oper. Res. 48(1):50-64.
43. Steel E, Angwin J (2010) On the Web's cutting edge, anonymity in name only. Wall Street Journal (August 4), http://online.wsj.com/news/articles/ SB10001424052748703294904575385532109190198.
44. Talluri K, van Ryzin GJ (2004) Revenue management under a general discrete choice model of consumer behavior. Management Sci. 50(1):15-33.
45. Talluri K, van Ryzin GJ (2004) The Theory and Practice of Revenue Management (Springer, New York).
46. Thompson D (2012) The 11 ways that consumers are hopeless at math. The Atlantic (July 6), http://www.theatlantic.com/business/archive/2012/07/the-11- ways-that-consumers-are-hopeless-at-math/259479/.
47. Topaloglu H (2013) Joint stocking and product offer decisions under the multinomial logit model. Production Oper. Management 22(5):1182-1199.
48. van Ryzin G, Mahajan S (1999) On the relationship between inventory costs and variety benefits in retail assortments. Management Sci. 45(11):1496-1509.
49. Wortham J (2012) Rather than share your location, Foursquare wants to suggest one. New York Times (June 7), http://www.nytimes.com/2012/06/07/ technology/in-app-overhaul-foursquare-shifts-focus-to-recommendations.html?-r=0.
50. Yao A (1977) Probabilistic computations: Toward a unified measure of complexity. Proc. 18th IEEE Sympos. Foundations of Comput. Sci. (IEEE Computer Society, Washington, DC), 222-227.