Abstract
Budget-feasible procurement has been a major paradigm in mechanism design since its introduction by Singer [24]. An auctioneer (buyer) with a strict budget constraint is interested in buying goods or services from a group of strategic agents (sellers). In many scenarios it makes sense to allow the auctioneer to only partially buy what an agent offers, e.g., an agent might have multiple copies of an item to sell, they might offer multiple levels of a service, or they may be available to perform a task for any fraction of a specified time interval. Nevertheless, the focus of the related literature has been on settings where each agent’s services are either fully acquired or not at all. A reason for this is that in settings with partial allocations, without any assumptions on the costs, there are strong inapproximability results (see, e.g., Chan and Chen [10], Anari et al. [5]). Under the mild assumption of being able to afford each agent entirely, we are able to circumvent such results. We design a polynomial-time, deterministic, truthful, budget-feasible, \((2+\sqrt{3})\)-approximation mechanism for the setting where each agent offers multiple levels of service and the auctioneer has a discrete separable concave valuation function. We then use this result to design a deterministic, truthful and budget-feasible mechanism for the setting where any fraction of a service can be acquired and the auctioneer’s valuation function is separable concave (i.e., the sum of concave functions). The approximation ratio of this mechanism depends on how “nice” the concave functions are, and is O(1) for valuation functions that are sums of O(1)-regular functions (e.g., functions like \(\log (1+x)\)). For the special case of a linear valuation function, we improve the best known approximation ratio from \(1+\phi \) (by Klumper and Schäfer [17]) to 2. This establishes a separation result between this setting and its indivisible counterpart.
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Notes
- 1.
We refer the reader to [6] for a rigorous treatment of the uniqueness property of Myerson’s characterization result.
- 2.
Our results very easily extend to the setting where there is a different (public) \(k_i\) associated with each agent i. We use a common k for the sake of presentation.
- 3.
Whenever we use one of these assumptions, we implicitly constrain the space of the (declared) cost profiles. That is, we assume that any agent who violates the respective condition is discarded up front from further considerations, e.g., by running a pre-processing step that removes such agents.
- 4.
Note that for \(k=1\), the problem reduces to the well-known 0-1 Knapsack Problem.
- 5.
It is not hard to see that the set \(Q_{ij}(\textbf{c}_{-i})\) is also closed and thus the supremum always exists.
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Acknowledgment
This work was supported by the Dutch Research Council (NWO) through its Open Technology Program, proj. no. 18938, and the Gravitation Project NETWORKS, grant no. 024.002.003. It has also been partially supported by project MIS 5154714 of the National Recovery and Resilience Plan Greece 2.0, funded by the European Union under the NextGenerationEU Program and the EU Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie Grant Agreement, grant no. 101034253. Moreover, it was supported by the “1st Call for HFRI Research Projects to support faculty members and researchers and the procurement of high-cost research equipment” (proj. no. HFRI-FM17-3512). Finally, part of this work was done during AT’s visit to the University of Essex that was supported by COST Action CA16228 (European Network for Game Theory).
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Amanatidis, G., Klumper, S., Markakis, E., Schäfer, G., Tsikiridis, A. (2024). Partial Allocations in Budget-Feasible Mechanism Design: Bridging Multiple Levels of Service and Divisible Agents. In: Garg, J., Klimm, M., Kong, Y. (eds) Web and Internet Economics. WINE 2023. Lecture Notes in Computer Science, vol 14413. Springer, Cham. https://doi.org/10.1007/978-3-031-48974-7_3
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