Methods for Handling Probability Constraints

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 19 in Methods of Nonsmooth Optimization in Stochastic Programming, 2025, pp 521-556 from Springer

Abstract: Abstract This chapter discusses various algorithms or declinations thereof for solving chance-constrained optimization problems. It begins with non-smooth approaches in the presence of convexity (for the feasible sets), then moves to a global optimization approach to (mixed-integer) joint chance-constrained optimization problems with right-hand side uncertainty, and finally discusses approximation techniques of different kinds, including Difference-of-Convex and CVaR approximations.

Keywords: Chance-constrained programming through non-linear programming methods; Optimization methods; Conservative models for chance-constraints (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_19

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DOI: 10.1007/978-3-031-84837-7_19

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