A bilevel model of taxation and its application to optimal highway pricing
Management Science
Approximation algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Edge Pricing of Multicommodity Networks for Heterogeneous Selfish Users
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
Tolls for Heterogeneous Selfish Users in Multicommodity Networks and Generalized Congestion Games
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
On profit-maximizing envy-free pricing
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Mechanism Design via Machine Learning
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Combination can be hard: approximability of the unique coverage problem
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Single-minded unlimited supply pricing on sparse instances
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Linear tolls suffice: new bounds and algorithms for tolls in single source networks
Theoretical Computer Science - Automata, languages and programming: Algorithms and complexity (ICALP-A 2004)
Approximation algorithms and online mechanisms for item pricing
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Algorithmic pricing via virtual valuations
Proceedings of the 8th ACM conference on Electronic commerce
Buying cheap is expensive: hardness of non-parametric multi-product pricing
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
The effectiveness of Stackelberg strategies and tolls for network congestion games
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Item pricing for revenue maximization
Proceedings of the 9th ACM conference on Electronic commerce
Optimal envy-free pricing with metric substitutability
Proceedings of the 9th ACM conference on Electronic commerce
Uniform Budgets and the Envy-Free Pricing Problem
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I
Computational Aspects of a 2-Player Stackelberg Shortest Paths Tree Game
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
A quasi-PTAS for profit-maximizing pricing on line graphs
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Near-optimal pricing in near-linear time
WADS'05 Proceedings of the 9th international conference on Algorithms and Data Structures
The stackelberg minimum spanning tree game
WADS'07 Proceedings of the 10th international conference on Algorithms and Data Structures
Specializations and generalizations of the stackelberg minimum spanning tree game
WINE'10 Proceedings of the 6th international conference on Internet and network economics
Improved hardness of approximation for stackelberg shortest-path pricing
WINE'10 Proceedings of the 6th international conference on Internet and network economics
The Stackelberg minimum spanning tree game on planar and bounded-treewidth graphs
Journal of Combinatorial Optimization
Hi-index | 0.00 |
In a Stackelberg pricing game a leader aims to set prices on a subset of a given collection of items, such as to maximize her revenue from a follower purchasing a feasible subset of the items. We focus on the case of computationally bounded followers who cannot optimize exactly over the range of all feasible subsets, but apply some publicly known algorithm to determine the set of items to purchase. This corresponds to general multi-dimensional pricing assuming that consumers cannot optimize over the full domain of their valuation functions but still aim to act rationally to the best of their ability.We consider two versions of this novel type of Stackelberg pricing games. Assuming that items are weighted objects and the follower seeks to purchase a min-cost selection of objects of some minimum weight (the Min-Knapsack problem) and uses a simple greedy 2-approximate algorithm, we show how an extension of the known single-price algorithm can be used to derive a polynomial-time (2 + 驴)-approximation algorithm for the leader's revenue maximization problem based on so-called near-uniform price assignments. We also prove the problem to be strongly NP-hard.Considering the case that items are subsets of some ground set which the follower seeks to cover (the Set-Cover problem) via a standard primal-dual approach, we prove that near-uniform price assignments fail to yield a good approximation guarantee. However, in the special case of elements with frequency 2 (the Vertex-Cover problem) it turns out that exact revenue maximization can be done in polynomial-time. This stands in sharp contrast to the fact that revenue maximization becomes APX-hard already for elements with frequency 3.