Multiagent Assortment Optimization in Sequential Matching Markets
References
- [1] (2011) Improved analysis of the greedy algorithm for stochastic matching. Inform. Processing Lett. 111(15):731–737.Crossref, Google Scholar
- [2] (2022) Parameterized approximations for the two-sided assortment optimization. Oper. Res. Lett. 50(4):399–406.Crossref, Google Scholar
- [3] (2023) Online assortment optimization for two-sided matching platforms. Management Sci. 69(4):2069–2087.Link, Google Scholar
- [4] (2018) The approximability of assortment optimization under ranking preferences. Oper. Res. 66(6):1661–1669.Link, Google Scholar
- [5] (2021) Managing congestion in matching markets. Manufacturing Service Oper. Management 23(3):620–636.Link, Google Scholar
- [6] (2020) Clearing matching markets efficiently: Informative signals and match recommendations. Management Sci. 66(5):2163–2193.Link, Google Scholar
- [7] (2022) Technical note—Assortment planning for two-sided sequential matching markets. Oper. Res. 70(5):2784–2803.Link, Google Scholar
- [8] (2001) Random utility models in marketing research: A survey. J. Bus. Res. 51(2):115–125.Crossref, Google Scholar
- [9] (2015) Pricing in ride-sharing platforms: A queueing-theoretic approach. EC’15: Proc. 16th ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 639.Google Scholar
- [10] (2012) When LP is the cure for your matching woes: Improved bounds for stochastic matchings. Algorithmica 63:733–762.Crossref, Google Scholar
- [11] (2020) Assortment optimisation under a general discrete choice model: A tight analysis of revenue-ordered assortments. Algorithmica 82(4):681–720.Crossref, Google Scholar
- [12] (2021) Surge pricing and its spatial supply response. Management Sci. 67(3):1350–1367.Link, Google Scholar
- [13] (2017) Guarantees for greedy maximization of non-submodular functions with applications. Precup D, Teh YW, eds. Proc. 34th Internat. Conf. Machine Learn., Proceedings of Machine Learning Research, vol. 70 (PMLR, New York), 498–507.Google Scholar
- [14] (2016) A Markov chain approximation to choice modeling. Oper. Res. 64(4):886–905.Link, Google Scholar
- [15] (2009) A column generation algorithm for choice-based network revenue management. Oper. Res. 57(3):769–784.Link, Google Scholar
- [16] (2021) Improved guarantees for offline stochastic matching via new ordered contention resolution schemes. Ranzato M, Beygelzimer A, Dauphin Y, Liang PS, Wortman Vaughan J, eds. NIPS’21: Proc. 35th Internat. Conf. Neural Inform. Processing Systems (Curran Associates Inc., Red Hook, NY), 27184–27195.Google Scholar
- [17] (2015) A tight linear time (1/2)-approximation for unconstrained submodular maximization. SIAM J. Comput. 44(5):1384–1402.Crossref, Google Scholar
- [18] (2011) Maximizing a monotone submodular function subject to a matroid constraint. SIAM J. Comput. 40(6):1740–1766.Crossref, Google Scholar
- [19] (2010) Dependent randomized rounding via exchange properties of combinatorial structures. Proc. 2010 IEEE 51st Annual Sympos. Foundations Comput. Sci. (IEEE Computer Society, Washington, DC), 575–584.Google Scholar
- [20] (2018) Weakly submodular maximization beyond cardinality constraints: Does randomization help greedy? Dy J, Krause A, eds. Proc. 35th Internat. Conf. Machine Learn., Proceedings of Machine Learning Research (PMLR, New York), 804–813.Google Scholar
- [21] (2009) Approximating matches made in heaven. Albers S, Marchetti-Spaccamela A, Matias Y, Nikoletseas S, Thomas W, eds. Automata, Languages Programming, ICALP 2009, Lecture Notes in Computer Science, vol. 5555 (Springer, Berlin, Heidelberg), 266–278.Google Scholar
- [22] (2012) Stochastic matching with commitment. Czumaj A, Mehlhorn K, Pitts A, Wattenhofer R, eds. Automata, Languages Programming, ICALP 2012, Lecture Notes in Computer Science, vol. 7391 (Springer, Berlin, Heidelberg), 822–833.Google Scholar
- [23] (2011) Submodular meets spectral: Greedy algorithms for subset selection, sparse approximation and dictionary selection. Getoor L, Scheffer T, eds. ICML’11: Proc. 28th Internat. Conf. Machine Learn. (Omnipress, Madison, WI), 1057–1064.Google Scholar
- [24] (2014) Assortment optimization under variants of the nested logit model. Oper. Res. 62(2):250–273.Link, Google Scholar
- [25] (2022) Technical note—Capacitated assortment optimization: Hardness and approximation. Oper. Res. 70(2):893–904.Link, Google Scholar
- [26] (2020) Constrained assortment optimization under the Markov chain–based choice model. Management Sci. 66(2):698–721.Link, Google Scholar
- [27] (2026) Two-sided assortment optimization: Adaptivity gaps and approximation algorithms, 2024. Oper. Res. Forthcoming.Google Scholar
- [28] (2011) A unified continuous greedy algorithm for submodular maximization. 2011 IEEE 52nd Annual Sympos. Foundations Comput. Sci. (IEEE, Piscataway, NJ), 570–579.Google Scholar
- [29] (2024) Near-optimal Bayesian online assortment of reusable resources. Oper. Res. 72(5):1861–1873.Link, Google Scholar
- [30] (2015) Search frictions and the design of online marketplaces. Third Conf. Auctions Market Mechanisms Their Appl. (Association for Computing Machinery, New York).Google Scholar
- [31] (2014) Constrained assortment optimization for the nested logit model. Management Sci. 60(10):2583–2601.Link, Google Scholar
- [32] (2019) Revenue Management and Pricing Analytics, International Series in Operations Research & Management Science, vol. 279 (Springer, New York).Crossref, Google Scholar
- [33] (2019) Beating greedy for stochastic bipartite matching. SODA’19: Proc. 30th Annual ACM-SIAM Sympos. Discrete Algorithms (Society for Industrial and Applied Mathematics, Philadelphia), 2841–2854.Google Scholar
- [34] (2014) Real-time optimization of personalized assortments. Management Sci. 60(6):1532–1551.Link, Google Scholar
- [35] (2022) Online assortment optimization with reusable resources. Management Sci. 68(7):4772–4785.Link, Google Scholar
- [36] (2025) Asymptotically optimal competitive ratio for online allocation of reusable resources. Oper. Res. 73(4):1897–1915.Link, Google Scholar
- [37] (2018) Competing by restricting choice: The case of search platforms. Management Sci. 64(8):3574–3594.Link, Google Scholar
- [38] (2021) Integrated optimization of bipartite matching and its stochastic behavior: New formulation and approximation algorithm via min-cost flow optimization. Proc. AAAI Conf. Artificial Intelligence, vol. 35 (AAAI Press, Washington, DC), 3796–3805.Google Scholar
- [39] (2010) Online labor markets. Saberi A, ed. Internet Network Econom., WINE 2010, Lecture Notes in Computer Science, vol. 6484 (Springer, Berlin, Heidelberg), 515–522.Google Scholar
- [40] (2017) The effects of algorithmic labor market recommendations: Evidence from a field experiment. J. Labor Econom. 35(2):345–385.Crossref, Google Scholar
- [41] (2021) Designing approximately optimal search on matching platforms. EC’21: Proc. 22nd ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 632–633.Google Scholar
- [42] (2021) Decentralized matching in a probabilistic environment. EC’21: Proc. 22nd ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 635–653.Google Scholar
- [43] (2021) Facilitating the search for partners on matching platforms. Management Sci. 67(10):5990–6029.Link, Google Scholar
- [44] (2013) Online submodular welfare maximization: Greedy is optimal. Proc. 24th Annual ACM-SIAM Sympos. Discrete Algorithms (Society for Industrial and Applied Mathematics, Philadelphia), 1216–1225.Google Scholar
- [45] (2008) Inapproximability results for combinatorial auctions with submodular utility functions. Algorithmica 52:3–18.Crossref, Google Scholar
- [46] (2008) Assortment planning: Review of literature and industry practice. Agrawal N, Smith S, eds. Retail Supply Chain Management, International Series in Operations Research & Management Science, vol. 122 (Springer, Boston), 99–153.Crossref, Google Scholar
- [47] (2019) Interlaced greedy algorithm for maximization of submodular functions in nearly linear time. Wallach HM, Larochelle H, Beygelzimer A, d’Alché-Buc F, Fox EB, eds. NIPS’19: Proc. 33rd Internat. Conf. Neural Inform. Processing Systems (Curran Associates Inc., Red Hook, NY), 2374–2384.Google Scholar
- [48] (2006) Combinatorial auctions with decreasing marginal utilities. Games Econom. Behav. 55(2):270–296.Crossref, Google Scholar
- [49] (2020) Higher market thickness reduces matching rate in online platforms: Evidence from a quasiexperiment. Management Sci. 66(1):271–289.Link, Google Scholar
- [50] (1965) Preference, utility and subjective probability. Luce RD, Bush, RR, Galanter EH, eds. Handbook of Mathematical Psychology, vol. 3 (Wiley, New York), 249–410.Google Scholar
- [51] (2020) Algorithms for online matching, assortment, and pricing with tight weight-dependent competitive ratios. Oper. Res. 68(6):1787–1803.Link, Google Scholar
- [52] (2022) Online policies for efficient volunteer crowdsourcing. Management Sci. 68(9):6572–6590.Link, Google Scholar
- [53] (2025) Online algorithms for matching platforms with multichannel traffic. Management Sci. 71(9):7674–7691.Link, Google Scholar
- [54] (1974) Conditional logit analysis of qualitative choice behavior. Zarembka P, ed. Frontiers in Econometrics (Academic Press, New York), 105–142.Google Scholar
- [55] (2012) Online matching with stochastic rewards. 2012 IEEE 53rd Annual Sympos. Foundations Comput. Sci. (IEEE, Piscataway, NJ), 728–737.Google Scholar
- [56] (2007) AdWords and generalized online matching. J. ACM 54(5):22-es.Crossref, Google Scholar
- [57] (2026) The dating heuristic: A provably strong matching algorithm for dating platforms. Manufacturing Service Oper. Management, ePub ahead of print March 27, https://doi.org/10.1287/msom.2024.1053.Link, Google Scholar
- [58] (2023) Improving match rates in dating markets through assortment optimization. Manufacturing Service Oper. Management 25(4):1304–1323.Link, Google Scholar
- [59] (2003) Platform competition in two-sided markets. J. Eur. Econom. Assoc. 1(4):990–1029.Crossref, Google Scholar
- [60] (2010) Dynamic assortment optimization with a multinomial logit choice model and capacity constraint. Oper. Res. 58(6):1666–1680.Link, Google Scholar
- [61] (2014) Assortment optimization under the multinomial logit model with random choice parameters. Production Oper. Management 23(11):2023–2039.Crossref, Google Scholar
- [62] (2019) Multivariate submodular optimization. Chaudhuri K, Salakhutdinov R, eds. Proc. 36th Internat. Conf. Machine Learn., Proceedings of Machine Learning Research, vol. 97 (PMLR, New York), 5599–5609.Google Scholar
- [63] (2023) Optimal matchmaking strategy in two-sided marketplaces. Management Sci. 69(3):1323–1340.Link, Google Scholar
- [64] (2025) Optimal match recommendations in two-sided marketplaces with endogenous prices. Management Sci. 71(9):7431–7448.Link, Google Scholar
- [65] (2018) Maximizing monotone submodular functions over the integer lattice. Math. Programming 172:539–563.Crossref, Google Scholar
- [66] (2021) Revenue-utility tradeoff in assortment optimization under the multinomial logit model with totally unimodular constraints. Management Sci. 67(5):2845–2869.Link, Google Scholar
- [67] (2004) Revenue management under a general discrete choice model of consumer behavior. Management Sci. 50(1):15–33.Link, Google Scholar
- [68] (1927) A law of comparative judgment. Psych. Rev. 34(4):273–286.Crossref, Google Scholar
- [69] (2013) Joint stocking and product offer decisions under the multinomial logit model. Production Oper. Management 22(5):1182–1199.Crossref, Google Scholar
- [70] (2008) Optimal approximation for the submodular welfare problem in the value oracle model. STOC’08: Proc. 40th Annual ACM Sympos. Theory Comput. (Association for Computing Machinery, New York), 67–74.Google Scholar
- [71] (1977) On the formation of travel demand models and economic evaluation measures of user benefit. Environment Planning A 9(3):285–344.Crossref, Google Scholar

