Marc C. Steinbach
Leibniz University of Hanover
62 Papers
380 Citations
Marc C. Steinbach is an academic researcher from Leibniz University of Hanover. The author has contributed to research in topics: Nonlinear programming & Computer science. The author has an hindex of 20, co-authored 56 publications. Previous affiliations of Marc C. Steinbach include Heidelberg University & Zuse Institute Berlin.
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Papers
Markowitz Revisited: Mean-Variance Models in Financial Portfolio Analysis
TL;DR: The interplay between objective and constraints in a number of single-period variants, including semivariance models are described, revealing the possibility of removing surplus money in future decisions, yielding approximate downside risk minimization.
Validation of nominations in gas network optimization: models, methods, and solutions
Marc E. Pfetsch,Armin Fügenschuh,Björn Geißler,Nina Geißler,Ralf Gollmer,Benjamin Hiller,Jesco Humpola,Thorsten Koch,Thomas Lehmann,Alex Martin,Antonio Morsi,Jessica Rövekamp,Lars Schewe,Martin Schmidt,Rüdiger Schultz,Robert Schwarz,Jonas Schweiger,Claudia Stangl,Marc C. Steinbach,Stefan Vigerske,Bernhard M. Willert +20 more
TL;DR: This article investigates methods to solve a fundamental task in gas transportation, namely the validation of nomination problem, and describes a two-stage approach to solve the resulting complex and numerically difficult nonconvex mixedinteger nonlinear feasibility problem.
Optimization models for operative planning in drinking water networks
TL;DR: A nonlinear mixed integer model and a nonlinear programming model with favorable properties for gradient-based optimization methods, based on smooth component models for the network elements are developed.
High detail stationary optimization models for gas networks
TL;DR: In this paper, the authors present stationary NLP type models of gas networks that are primarily designed to include detailed nonlinear physics in the final optimization steps for mid-term planning problems after fixing discrete decisions with coarsely approximated physics.
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Exploiting Invariants in the Numerical Solution of Multipoint Boundary Value Problems for DAE
TL;DR: Generalizations of the "internal numerical differentiation" technique to DAE with invariants and a new multistage least squares decomposition technique for DAE boundary value problems are developed, which are implemented in the multiple shooting code PARFIT and in the collocation code COLFIT.
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