Algorithmic mechanism design (extended abstract)
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Truth revelation in approximately efficient combinatorial auctions
Proceedings of the 1st ACM conference on Electronic commerce
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SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
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STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
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SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
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Operations Research
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SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
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ACM SIGecom Exchanges
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Proceedings of the 9th ACM conference on Electronic commerce
Reducing mechanism design to algorithm design via machine learning
Journal of Computer and System Sciences
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SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
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WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
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IEICE - Transactions on Information and Systems
On Hardness of Pricing Items for Single-Minded Bidders
APPROX '09 / RANDOM '09 Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
Implementing the maximum of monotone algorithms
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
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WINE '09 Proceedings of the 5th 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
Bundle pricing with comparable items
ESA'07 Proceedings of the 15th annual European conference on Algorithms
A theory of loss-leaders: making money by pricing below cost
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Pricing commodities, or how to sell when buyers have restricted valuations
WAOA'07 Proceedings of the 5th international conference on Approximation and online algorithms
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Envy-free pricing with general supply constraints
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Optimal Envy-Free Pricing with Metric Substitutability
SIAM Journal on Computing
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On the hardness of pricing loss-leaders
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Pricing on paths: a PTAS for the highway problem
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Revenue maximizing envy-free multi-unit auctions with budgets
Proceedings of the 13th ACM Conference on Electronic Commerce
Optimal bundle pricing with monotonicity constraint
Operations Research Letters
Buying Cheap Is Expensive: Approximability of Combinatorial Pricing Problems
SIAM Journal on Computing
A QPTAS for ε-envy-free profit-maximizing pricing on line graphs
ICALP'12 Proceedings of the 39th international colloquium conference on Automata, Languages, and Programming - Volume Part II
On the complexity of the highway problem
Theoretical Computer Science
A path-decomposition theorem with applications to pricing and covering on trees
ESA'12 Proceedings of the 20th Annual European conference on Algorithms
Envy-free pricing in multi-item markets
ACM Transactions on Algorithms (TALG)
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We deal with the problem of finding profit-maximizing prices for a finite number of distinct goods, assuming that of each good an unlimited number of copies is available, or that goods can be reproduced at no cost (e.g., digital goods). Consumers specify subsets of the goods and the maximum prices they are willing to pay. In the considered single-minded case every consumer is interested in precisely one such subset. If the goods are the edges of a graph and consumers are requesting to purchase paths in this graph, then we can think of the problem as pricing computer network connections or transportation links.We start by showing weak NP-hardness of the very restricted case in which the requested subsets are nested, i.e., contained inside each other or non-intersecting, thereby resolving the previously open question whether the problem remains NP-hard when the underlying graph is simply a line. Using a reduction inspired by this result we present an approximation preserving reduction that proves APX-hardness even for very sparse instances defined on general graphs, where the number of requests per edge is bounded by a constant B and no path is longer than some constant l. On the algorithmic side we first present an O(log l + log B)-approximation algorithm that (almost) matches the previously best known approximation guarantee in the general case, but is especially well suited for sparse problem instances. Using a new upper bounding technique we then give an O(l2)-approximation, which is the first algorithm for the general problem with an approximation ratio that does not depend on B.