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Dynamic Allocation and PricingA Mechanism Design Approach$
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Alex Gershkov and Benny Moldovanu

Print publication date: 2015

Print ISBN-13: 9780262028400

Published to MIT Press Scholarship Online: May 2016

DOI: 10.7551/mitpress/9780262028400.001.0001

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The Stochastic and Dynamic Knapsack Model

The Stochastic and Dynamic Knapsack Model

Chapter:
(p.73) 4 The Stochastic and Dynamic Knapsack Model
Source:
Dynamic Allocation and Pricing
Author(s):

Alex Gershkov

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262028400.003.0004

In this chapter the authors characterize the revenue maximizing policy in the dynamic and stochastic knapsack problem where a given capacity needs to be allocated by a given deadline to sequentially arriving agents. Each agent is described by a two-dimensional type that reflects his capacity requirement and his willingness to pay per unit of capacity. Types are private information. The authors first characterize implementable policies. Then they solve the revenue maximization problem for the special case where there is private information about per-unit values, but weights are observable. After that they derive two sets of additional conditions on the joint distribution of values and weights under which the revenue maximizing policy for the case with observable weights is implementable, and thus optimal also for the case with two-dimensional private information. Finally, the authors analyze a simple policy for which per-unit prices vary with requested weight but do not vary with time. Its implementation requirements are similar to those of the optimal policy and it turns out to be asymptotically revenue maximizing when available capacity/ time to the deadline both go to infinity.

Keywords:   Revenue maximization, Knapsack, multi-dimensional types

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