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Conference Paper: Achieving Hierarchy-Free Approximation for Bilevel Programs With Equilibrium Constraints
Title | Achieving Hierarchy-Free Approximation for Bilevel Programs With Equilibrium Constraints |
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Authors | |
Issue Date | 2023 |
Citation | Proceedings of Machine Learning Research, 2023, v. 202, p. 19689-19729 How to Cite? |
Abstract | In this paper, we develop an approximation scheme for solving bilevel programs with equilibrium constraints, which are generally difficult to solve. Among other things, calculating the first-order derivative in such a problem requires differentiation across the hierarchy, which is computationally intensive, if not prohibitive. To bypass the hierarchy, we propose to bound such bilevel programs, equivalent to multiple-followers Stackelberg games, with two new hierarchy-free problems: a T-step Cournot game and a T-step monopoly model. Since they are standard equilibrium or optimization problems, both can be efficiently solved via first-order methods. Importantly, we show that the bounds provided by these problems - the upper bound by the T-step Cournot game and the lower bound by the T-step monopoly model - can be made arbitrarily tight by increasing the step parameter T for a wide range of problems. We prove that a small T usually suffices under appropriate conditions to reach an approximation acceptable for most practical purposes. Eventually, the analytical insights are highlighted through numerical examples. |
Persistent Identifier | http://hdl.handle.net/10722/351478 |
DC Field | Value | Language |
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dc.contributor.author | Li, Jiayang | - |
dc.contributor.author | Yu, Jing | - |
dc.contributor.author | Liu, Boyi | - |
dc.contributor.author | Nie, Yu | - |
dc.contributor.author | Wang, Zhaoran | - |
dc.date.accessioned | 2024-11-20T03:56:33Z | - |
dc.date.available | 2024-11-20T03:56:33Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Proceedings of Machine Learning Research, 2023, v. 202, p. 19689-19729 | - |
dc.identifier.uri | http://hdl.handle.net/10722/351478 | - |
dc.description.abstract | In this paper, we develop an approximation scheme for solving bilevel programs with equilibrium constraints, which are generally difficult to solve. Among other things, calculating the first-order derivative in such a problem requires differentiation across the hierarchy, which is computationally intensive, if not prohibitive. To bypass the hierarchy, we propose to bound such bilevel programs, equivalent to multiple-followers Stackelberg games, with two new hierarchy-free problems: a T-step Cournot game and a T-step monopoly model. Since they are standard equilibrium or optimization problems, both can be efficiently solved via first-order methods. Importantly, we show that the bounds provided by these problems - the upper bound by the T-step Cournot game and the lower bound by the T-step monopoly model - can be made arbitrarily tight by increasing the step parameter T for a wide range of problems. We prove that a small T usually suffices under appropriate conditions to reach an approximation acceptable for most practical purposes. Eventually, the analytical insights are highlighted through numerical examples. | - |
dc.language | eng | - |
dc.relation.ispartof | Proceedings of Machine Learning Research | - |
dc.title | Achieving Hierarchy-Free Approximation for Bilevel Programs With Equilibrium Constraints | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.scopus | eid_2-s2.0-85174394209 | - |
dc.identifier.volume | 202 | - |
dc.identifier.spage | 19689 | - |
dc.identifier.epage | 19729 | - |
dc.identifier.eissn | 2640-3498 | - |