We present a new algorithm for the solution of Generalized Nash Equilibrium Problems. This hybrid method combines the robustness of a potential reduction algorithm and the local quadratic convergence rate of the LP-Newton method. We base our local convergence theory on a local error bound and provide a new sufficient condition for it to hold that is weaker than known ones. In particular, this condition implies neither local uniqueness of a solution nor strict complementarity. We also report promising numerical results. © 2013 Springer Science+Business Media New York.

A new error bound result for Generalized Nash Equilibrium Problems and its algorithmic application / Dreves, Axel; Facchinei, Francisco; Fischer, Andreas; Herrich, Markus. - In: COMPUTATIONAL OPTIMIZATION AND APPLICATIONS. - ISSN 0926-6003. - STAMPA. - 59:(2013), pp. 1-22. [10.1007/s10589-013-9586-z]

A new error bound result for Generalized Nash Equilibrium Problems and its algorithmic application

FACCHINEI, Francisco;
2013

Abstract

We present a new algorithm for the solution of Generalized Nash Equilibrium Problems. This hybrid method combines the robustness of a potential reduction algorithm and the local quadratic convergence rate of the LP-Newton method. We base our local convergence theory on a local error bound and provide a new sufficient condition for it to hold that is weaker than known ones. In particular, this condition implies neither local uniqueness of a solution nor strict complementarity. We also report promising numerical results. © 2013 Springer Science+Business Media New York.
2013
generalized nash equilibrium problem; generalized nash equilibrium problem ·; global convergence; local error bound condition; local quadratic convergence; lp-newton method; potential reduction algorithm; · local quadratic convergence ·
01 Pubblicazione su rivista::01a Articolo in rivista
A new error bound result for Generalized Nash Equilibrium Problems and its algorithmic application / Dreves, Axel; Facchinei, Francisco; Fischer, Andreas; Herrich, Markus. - In: COMPUTATIONAL OPTIMIZATION AND APPLICATIONS. - ISSN 0926-6003. - STAMPA. - 59:(2013), pp. 1-22. [10.1007/s10589-013-9586-z]
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