From Welfare to Utility: Generalized Objectives in Budget-Feasible Procurement

Alon Eden, Kira Goldner, Eldar Kerner, Thodoris Tsilivis
Proceedings of the 43rd International Conference on Machine Learning, PMLR 306:27594-27626, 2026.

Abstract

We study mechanism design for the budget-feasible procurement problem, a natural problem that arises when a buyer wants to procure goods or services from multiple strategic sellers who each have a cost to provide that service, the buyer has a value for each service procured, but is constrained by a budget. In contrast to prior work, which has focused on buyer value maximization for this problem, we solve for optimal and approximately-optimal mechanisms for the objectives of buyer utility (value of procured services minus payments), welfare (value minus production costs), and generalizations of the two. For welfare, we design a simple mechanism that obtains a constant-factor approximation for the prior-free (worst-case) setting. As prior-free mechanisms fail to provide any guarantee for utility, even for a single seller, we consider Bayesian settings, where the buyer has distributional knowledge over sellers’ costs. We first provide a utility-optimal mechanism that satisfies the buyer’s budget constraint in expectation, then we show how to modify the mechanism to satisfy the budget constraint ex-post, for every realization of seller costs, while still obtaining near-optimal utility guarantees. Finally, we generalize our mechanisms to other objectives.

Cite this Paper

BibTeX
@InProceedings{pmlr-v306-eden26a, title = {From Welfare to Utility: Generalized Objectives in Budget-Feasible Procurement}, author = {Eden, Alon and Goldner, Kira and Kerner, Eldar and Tsilivis, Thodoris}, booktitle = {Proceedings of the 43rd International Conference on Machine Learning}, pages = {27594--27626}, year = {2026}, editor = {Zhang, Tong and Dudik, Miroslav and Jaggi, Martin and Agarwal, Alekh and Li, Sharon and Schuurmans, Dale and Zhu, Jerry and Berkenkamp, Felix and Dong, Hanze and Bietti, Alberto}, volume = {306}, series = {Proceedings of Machine Learning Research}, month = {06--11 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v306/main/assets/eden26a/eden26a.pdf}, url = {https://proceedings.mlr.press/v306/eden26a.html}, abstract = {We study mechanism design for the budget-feasible procurement problem, a natural problem that arises when a buyer wants to procure goods or services from multiple strategic sellers who each have a cost to provide that service, the buyer has a value for each service procured, but is constrained by a budget. In contrast to prior work, which has focused on buyer value maximization for this problem, we solve for optimal and approximately-optimal mechanisms for the objectives of buyer utility (value of procured services minus payments), welfare (value minus production costs), and generalizations of the two. For welfare, we design a simple mechanism that obtains a constant-factor approximation for the prior-free (worst-case) setting. As prior-free mechanisms fail to provide any guarantee for utility, even for a single seller, we consider Bayesian settings, where the buyer has distributional knowledge over sellers’ costs. We first provide a utility-optimal mechanism that satisfies the buyer’s budget constraint in expectation, then we show how to modify the mechanism to satisfy the budget constraint ex-post, for every realization of seller costs, while still obtaining near-optimal utility guarantees. Finally, we generalize our mechanisms to other objectives.} }
Endnote
%0 Conference Paper %T From Welfare to Utility: Generalized Objectives in Budget-Feasible Procurement %A Alon Eden %A Kira Goldner %A Eldar Kerner %A Thodoris Tsilivis %B Proceedings of the 43rd International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2026 %E Tong Zhang %E Miroslav Dudik %E Martin Jaggi %E Alekh Agarwal %E Sharon Li %E Dale Schuurmans %E Jerry Zhu %E Felix Berkenkamp %E Hanze Dong %E Alberto Bietti %F pmlr-v306-eden26a %I PMLR %P 27594--27626 %U https://proceedings.mlr.press/v306/eden26a.html %V 306 %X We study mechanism design for the budget-feasible procurement problem, a natural problem that arises when a buyer wants to procure goods or services from multiple strategic sellers who each have a cost to provide that service, the buyer has a value for each service procured, but is constrained by a budget. In contrast to prior work, which has focused on buyer value maximization for this problem, we solve for optimal and approximately-optimal mechanisms for the objectives of buyer utility (value of procured services minus payments), welfare (value minus production costs), and generalizations of the two. For welfare, we design a simple mechanism that obtains a constant-factor approximation for the prior-free (worst-case) setting. As prior-free mechanisms fail to provide any guarantee for utility, even for a single seller, we consider Bayesian settings, where the buyer has distributional knowledge over sellers’ costs. We first provide a utility-optimal mechanism that satisfies the buyer’s budget constraint in expectation, then we show how to modify the mechanism to satisfy the budget constraint ex-post, for every realization of seller costs, while still obtaining near-optimal utility guarantees. Finally, we generalize our mechanisms to other objectives.
APA
Eden, A., Goldner, K., Kerner, E. & Tsilivis, T.. (2026). From Welfare to Utility: Generalized Objectives in Budget-Feasible Procurement. Proceedings of the 43rd International Conference on Machine Learning, in Proceedings of Machine Learning Research 306:27594-27626 Available from https://proceedings.mlr.press/v306/eden26a.html.

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