Applications of the proximal difference-of-convex algorithm with extrapolation in optimal correction

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Shahsavari Samira; Ketabchi Saeed

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Journal Paper

Paper Information

Journal: Journal of Mathematical Modeling Year:2023 | Volume:11 | Issue:1 Page(s): 35-54

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Information Journal Paper

Title

Applications of the proximal difference-of-convex algorithm with extrapolation in optimal correction

Author(s)

Shahsavari Samira | Ketabchi Saeed | Issue Writer Certificate

Keywords

Proximal difference-of-convex

extrapolation

classical obstacle problem

equilibrium problems

linear inequalities

nonconvex

level-bounded

Abstract

This paper proposes a Proximal difference-of-convex algorithm with extrapolation ($PDCA_e$) based on Dinkelbach's approach for the optimal correction of two types of piecewise linear systems, classical obstacle problems and equilibrium problems, and linear inequalities. Using Dinkelbach's theorem leads to getting the roots of two single-variable functions. Considering the non-convex and level-bounded properties of the obtained problems, we use a Proximal difference-of-convex algorithm programming to solve them. The experimental results on several randomly generated test problems show that the $PDCA_e$-generalized Newton method outperforms other methods for both feasible and infeasible cases.

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