A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking

Shisheng  Cui; B. Franci; S. Grammatico; Uday V.  Shanbhag; Mathias Staudigl

doi:10.1109/CDC45484.2021.9682905

A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking

Shisheng Cui, B. Franci, S. Grammatico, Uday V. Shanbhag, Mathias Staudigl

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

Abstract

We propose a new operator splitting algorithm for distributed Nash equilibrium seeking under stochastic uncertainty, featuring relaxation and inertial effects. The proposed algorithm is derived from a forward-backward-forward scheme for solving structured monotone inclusion problems with Lipschitz continuous and monotone pseudogradient operator. To the best of our knowledge, this is the first distributed generalized Nash equilibrium seeking algorithm featuring acceleration techniques in stochastic Nash equilibrium problems without assuming cocoercivity. Numerical examples illustrate the effect of inertia and relaxation on the performance of our proposed algorithm.

Original language	English
Title of host publication	Proceedings of the 60th IEEE Conference on Decision and Control (CDC 2021)
Publisher	IEEE
Pages	197-202
ISBN (Print)	978-1-6654-3659-5
DOIs	https://doi.org/10.1109/CDC45484.2021.9682905
Publication status	Published - 2021
Event	60th IEEE Conference on Decision and Control (CDC 2021) - Austin, United States Duration: 14 Dec 2021 → 17 Dec 2021

Conference

Conference	60th IEEE Conference on Decision and Control (CDC 2021)
Country/Territory	United States
City	Austin
Period	14/12/21 → 17/12/21

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10.1109/CDC45484.2021.9682905

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title = "A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking",

abstract = "We propose a new operator splitting algorithm for distributed Nash equilibrium seeking under stochastic uncertainty, featuring relaxation and inertial effects. The proposed algorithm is derived from a forward-backward-forward scheme for solving structured monotone inclusion problems with Lipschitz continuous and monotone pseudogradient operator. To the best of our knowledge, this is the first distributed generalized Nash equilibrium seeking algorithm featuring acceleration techniques in stochastic Nash equilibrium problems without assuming cocoercivity. Numerical examples illustrate the effect of inertia and relaxation on the performance of our proposed algorithm.",

author = "Shisheng Cui and B. Franci and S. Grammatico and Shanbhag, {Uday V.} and Mathias Staudigl",

year = "2021",

doi = "10.1109/CDC45484.2021.9682905",

language = "English",

isbn = "978-1-6654-3659-5",

pages = "197--202",

booktitle = "Proceedings of the 60th IEEE Conference on Decision and Control (CDC 2021)",

publisher = "IEEE",

address = "United States",

note = "60th IEEE Conference on Decision and Control (CDC 2021) ; Conference date: 14-12-2021 Through 17-12-2021",

}

Cui, S, Franci, B, Grammatico, S, Shanbhag, UV & Staudigl, M 2021, A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking. in Proceedings of the 60th IEEE Conference on Decision and Control (CDC 2021). IEEE, pp. 197-202, 60th IEEE Conference on Decision and Control (CDC 2021), Austin, Texas, United States, 14/12/21. https://doi.org/10.1109/CDC45484.2021.9682905

A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking. / Cui, Shisheng ; Franci, B.; Grammatico, S. et al.
Proceedings of the 60th IEEE Conference on Decision and Control (CDC 2021). IEEE, 2021. p. 197-202.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Staudigl, Mathias

PY - 2021

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N2 - We propose a new operator splitting algorithm for distributed Nash equilibrium seeking under stochastic uncertainty, featuring relaxation and inertial effects. The proposed algorithm is derived from a forward-backward-forward scheme for solving structured monotone inclusion problems with Lipschitz continuous and monotone pseudogradient operator. To the best of our knowledge, this is the first distributed generalized Nash equilibrium seeking algorithm featuring acceleration techniques in stochastic Nash equilibrium problems without assuming cocoercivity. Numerical examples illustrate the effect of inertia and relaxation on the performance of our proposed algorithm.

AB - We propose a new operator splitting algorithm for distributed Nash equilibrium seeking under stochastic uncertainty, featuring relaxation and inertial effects. The proposed algorithm is derived from a forward-backward-forward scheme for solving structured monotone inclusion problems with Lipschitz continuous and monotone pseudogradient operator. To the best of our knowledge, this is the first distributed generalized Nash equilibrium seeking algorithm featuring acceleration techniques in stochastic Nash equilibrium problems without assuming cocoercivity. Numerical examples illustrate the effect of inertia and relaxation on the performance of our proposed algorithm.

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DO - 10.1109/CDC45484.2021.9682905

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BT - Proceedings of the 60th IEEE Conference on Decision and Control (CDC 2021)

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T2 - 60th IEEE Conference on Decision and Control (CDC 2021)

Y2 - 14 December 2021 through 17 December 2021

ER -

A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking

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