A dual approach for dynamic pricing in multi-demand markets

Dynamic pricing schemes were introduced as an alternative to posted-price mechanisms. In contrast to static models, the dynamic setting allows to update the prices between buyerarrivals based on the remaining sets of items and buyers, and so it is capable of maximizing social welfare without the need for a central coordinator. In this paper, we study the existence of optimal dynamic pricing schemes in combinatorial markets. In particular, we concentrate on multi-demand valuations, a natural extension of unit-demand valuations. The proposed approach is based on computing an optimal dual solution of the maximum social welfare problem with distinguished structural properties. Our contribution is twofold. By relying on an optimal dual solution, we show the existence of optimal dynamic prices in unit-demand markets and in multi-demand markets up to three buyers, thus giving new interpretations of results of Cohen-Addad et al. [8] and Berger et al. [2], respectively. Furthermore, we provide an optimal dynamic pricing scheme for bi-demand valuations with an arbitrary number of buyers. In all cases, our proofs also provide efficient algorithms for determining the optimal dynamic prices.

[1]  Amos Fiat,et al.  The Invisible Hand of Dynamic Market Pricing , 2015, EC.

[2]  Michal Feldman,et al.  Combinatorial Walrasian Equilibrium , 2016, SIAM J. Comput..

[3]  Shuchi Chawla,et al.  The power of randomness in bayesian optimal mechanism design , 2010, EC '10.

[4]  Shuchi Chawla,et al.  Multi-parameter mechanism design and sequential posted pricing , 2010, BQGT.

[5]  Noam Nisan,et al.  The communication requirements of efficient allocations and supporting prices , 2006, J. Econ. Theory.

[6]  Shuchi Chawla,et al.  Pricing for Online Resource Allocation: Intervals and Paths , 2019, SODA.

[7]  Faruk Gul,et al.  WALRASIAN EQUILIBRIUM WITH GROSS SUBSTITUTES , 1999 .

[8]  Liad Blumrosen,et al.  Posted prices vs. negotiations: an asymptotic analysis , 2008, EC '08.

[9]  Theodore Groves,et al.  Incentives in Teams , 1973 .

[10]  Alexander Schrijver,et al.  Combinatorial optimization. Polyhedra and efficiency. , 2003 .

[11]  Paul Dütting,et al.  Posted Prices, Smoothness, and Combinatorial Prophet Inequalities , 2016, ArXiv.

[12]  V. Crawford,et al.  Job Matching, Coalition Formation, and Gross Substitutes , 1982 .

[13]  D. König Über Graphen und ihre Anwendung auf Determinantentheorie und Mengenlehre , 1916 .

[14]  Justin Hsu,et al.  Do prices coordinate markets? , 2015, SECO.

[15]  E. H. Clarke Multipart pricing of public goods , 1971 .

[16]  Tim Roughgarden,et al.  Pricing Multi-unit Markets , 2018, WINE.

[17]  William Vickrey,et al.  Counterspeculation, Auctions, And Competitive Sealed Tenders , 1961 .

[18]  Naonori Kakimura,et al.  Market Pricing for Matroid Rank Valuations , 2020, ISAAC.

[19]  Michal Feldman,et al.  Combinatorial Auctions via Posted Prices , 2014, SODA.

[20]  Paul Dütting,et al.  Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs , 2016, 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS).

[21]  Uriel Feige,et al.  Max-min greedy matching , 2018, NetEcon@SIGMETRICS.

[22]  Kazuo Murota,et al.  M-Convex Function on Generalized Polymatroid , 1999, Math. Oper. Res..

[23]  Léon Walras Éléments d'économie politique pure, ou, Théorie de la richesse sociale , 1976 .