TY - JOUR A1 - Witzig, Jakob A1 - Berthold, Timo T1 - Conflict Analysis for MINLP T2 - INFORMS Journal on Computing N2 - The generalization of MIP techniques to deal with nonlinear, potentially non-convex, constraints have been a fruitful direction of research for computational MINLP in the last decade. In this paper, we follow that path in order to extend another essential subroutine of modern MIP solvers towards the case of nonlinear optimization: the analysis of infeasible subproblems for learning additional valid constraints. To this end, we derive two different strategies, geared towards two different solution approaches. These are using local dual proofs of infeasibility for LP-based branch-and-bound and the creation of nonlinear dual proofs for NLP-based branch-and-bound, respectively. We discuss implementation details of both approaches and present an extensive computational study, showing that both techniques can significantly enhance performance when solving MINLPs to global optimality. Y1 - 2021 UR - https://opus4.kobv.de/opus4-zib/frontdoor/index/index/docId/8062 VL - 33 IS - 2 SP - 421 EP - 435 ER -