The optimization-based design of energy systems generally leads to mixed-integer nonlinear programming (MINLP) problems. In recent years, a surge of interest in (non-convex) MINLP problems in the mathematical optimization community produced remarkable algorithmic progress and triggered new developments, in particular new implementations.
To benefit most from these advances, engineers and mathematicians should tie up, each contributing their own expertise. Aim of this workshop is to bring together researchers from both fields to learn about the latest work and to foster collaborations.
The workshop consists of three keynotes delivered by distinguished scholars, complemented by invited talks on recent work in the area. The workshop is supported by the DFG Excellence Initiative in the context of a seed fund project of the chairs of Operations Research, Discrete Optimization, and Technical Thermodynamics at RWTH Aachen University.
Keynotes of Invited Speakers
Prof. Dr. Zdravko Kravanja
Faculty of Chemistry and Chemical Engineering, University of Maribor, Slovenia,
Leader of the Laboratory for Process System Engineering and Sustainable Development
Keynote: Robust MINLP for solving complex synthesis problems (Abstract) To solve the challenging MINLP problems arising in energy and related systems engineering, efficient strategies are required. In this talk, we discuss strategies such as MINLP with mixed-integer translation of variables, strategies for multiple level MINLP, bi- or multiple-level global MINLP, MINLP when applying implicit and explicit model formulation. In addition, we highlight the implementation of these approaches in computer package MIPSYN and present some applications.
Prof. Dr. Jeffrey T. Linderoth
Professor in the Department of Industrial and Systems Engineering and the Department of Computer Sciences, University of Wisconsin-Madison, USA
Keynote: Mixed-Integer Nonlinear Optimization: Applications, Algorithms, and Computation (Abstract) Mixed-integer nonlinear programming problems (MINLPs) combine the combinatorial complexity of discrete decisions with the numerical challenges of nonlinear functions. In this talk, we will describe applications of MINLP in science and engineering, demonstrate the importance of building "good" MINLP models, discuss numerical techniques for solving MINLP, and survey the forefront of ongoing research topics in this important and emerging area.
Dr. Stefan Vigerske
GAMS Software GmbH,
Zuse Institute Berlin
Global Mixed-Integer Optimization: Algorithms and Applications in Energy and Processes
Dispatch Optimization of Thermal Power Plants considering Non-Linear Constraints
Optimal Power Flow as a Polynomial Optimization Problem
Modelling and optimization of decentralized energy supply systems
Adaptive Discretization of Nonlinear Optimization Models for Energy Supply Systems