Combinatorial walrasian equilibrium

Michal Feldman, Nick Gravin, Brendan Lucier

Research output: Contribution to journalArticlepeer-review


We study a combinatorial market design problem, where a collection of indivisible objects is to be priced and sold to potential buyers subject to equilibrium constraints. The classic solution concept for such problems is Walrasian equilibrium (WE), which provides a simple and transparent pricing structure that achieves optimal social welfare. The main weakness of the WE notion is that it exists only in very restrictive cases. To overcome this limitation, we introduce the notion of a combinatorial Walrasian equilibium (CWE), a natural relaxation of WE. The difference between a CWE and a (noncombinatorial) WE is that the seller can package the items into indivisible bundles prior to sale, and the market does not necessarily clear. We show that every valuation profile admits a CWE that obtains at least half the optimal (unconstrained) social welfare. Moreover, we devise a polynomial time algorithm that, given an arbitrary allocation, computes a CWE that achieves at least half its welfare. Thus, the economic problem of finding a CWE with high social welfare reduces to the algorithmic problem of social-welfare approximation. In addition, we show that every valuation profile admits a CWE that extracts a logarithmic fraction of the optimal welfare as revenue. Finally, to motivate the use of bundles, we establish strong lower bounds when the seller is restricted to using item prices only. The strength of our results derives partly from their generality- our results hold for arbitrary valuations that may exhibit complex combinations of substitutes and complements.

Original languageEnglish
Pages (from-to)29-48
Number of pages20
JournalSIAM Journal on Computing
Issue number1
StatePublished - 2016


  • Approximation
  • Combinatorial auctions
  • Envy-free
  • Walrasian equilibrium

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)


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