Universal Method of Searching for Equilibria and Stochastic Equilibria in Transportation Networks


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Abstract

A universal method of searching for usual and stochastic equilibria in congestion population games is proposed. The Beckmann and stable dynamics models of an equilibrium flow distribution over paths are considered. A search for Nash(–Wardrop) stochastic equilibria leads to entropy-regularized convex optimization problems. Efficient solutions of such problems, more exactly, of their duals are sought by applying a recently proposed universal primal-dual gradient method, which is optimally and adaptively tuned to the smoothness of the problem under study.

About the authors

D. R. Baimurzina

Moscow Institute of Physics and Technology; Skolkovo Innovation Center

Author for correspondence.
Email: dilyara.rimovna@gmail.com
Russian Federation, Dolgoprudnyi, Moscow oblast, 141700; Moscow, 143026

A. V. Gasnikov

Moscow Institute of Physics and Technology; Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences

Author for correspondence.
Email: gasnikov.av@mipt.ru
Russian Federation, Dolgoprudnyi, Moscow oblast, 141700; Moscow, 127051

E. V. Gasnikova

Moscow Institute of Physics and Technology

Author for correspondence.
Email: egasnikova@yandex.ru
Russian Federation, Dolgoprudnyi, Moscow oblast, 141700

P. E. Dvurechensky

Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences; Weierstrass Institute for Applied Analysis and Stochastics

Author for correspondence.
Email: dvurechensky@iitp.ru
Russian Federation, Moscow, 127051; Berlin, 410117

E. I. Ershov

Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences

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Email: e.i.ershov@gmail.com
Russian Federation, Moscow, 127051

M. B. Kubentaeva

Moscow Institute of Physics and Technology

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Email: kubikmeruza@yandex.ru
Russian Federation, Dolgoprudnyi, Moscow oblast, 141700

A. A. Lagunovskaya

Moscow Institute of Physics and Technology

Author for correspondence.
Email: a.lagunovskaya@phystech.edu
Russian Federation, Dolgoprudnyi, Moscow oblast, 141700

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