Methods for Non-linearly Constrained Non-smooth Optimization Problems

Wim Stefanus Ackooij and Welington Luis de Oliveira
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Wim Stefanus Ackooij: Électricité de France (EDF R&D)
Welington Luis de Oliveira: Mines Paris - PSL

Chapter Chapter 12 in Methods of Nonsmooth Optimization in Stochastic Programming, 2025, pp 375-412 from Springer

Abstract: Abstract In this chapter, we present approaches for handling convex optimization problems featuring convex constraints. In particular, the latter are not assumed to be “known” analytically. That is, one can devise computational procedure to evaluate these constraints and obtain first-order information, but the constraints are not readily incorporated immediately within an optimization problem. We present various extensions of bundle methods to this setting as well as the supporting hyperplane method and a stabilized variant thereof.

Keywords: Non-smooth optimization; Non-linear constraints; Bundle methods; Supporting hyperplane methods (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-031-84837-7_12

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DOI: 10.1007/978-3-031-84837-7_12

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