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Journal Articles Journal of Optimization Theory and Applications Year : 2024

Relaxed-Inertial Proximal Point Algorithms for Nonconvex Equilibrium Problems with Applications

Abstract

We propose a relaxed-inertial proximal point algorithm for solving equilibrium problems involving bifunctions which satisfy in the second variable a generalized convexity notion called strong quasiconvexity, introduced by Polyak in 1966. The method is suitable for solving mixed variational inequalities and inverse mixed variational inequalities involving strongly quasiconvex functions, as these can be written as special cases of equilibrium problems. Numerical experiments where the performance of the proposed algorithm outperforms the one of the standard proximal point methods are provided, too.
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Dates and versions

hal-04429671 , version 1 (31-01-2024)

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  • HAL Id : hal-04429671 , version 1

Cite

Sorin-Mihai Grad, Felipe Lara, Raúl Marcavillaca. Relaxed-Inertial Proximal Point Algorithms for Nonconvex Equilibrium Problems with Applications. Journal of Optimization Theory and Applications, inPress. ⟨hal-04429671⟩
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