6618
eng
reportzib
0
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2017-12-18
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Optimizing Large-Scale Linear Energy System Problems with Block Diagonal Structure by Using Parallel Interior-Point Methods
Current linear energy system models (ESM) acquiring to provide sufficient detail and reliability frequently bring along problems of both high intricacy and increasing scale. Unfortunately, the size and complexity of these problems often prove to be intractable even for commercial state-of-the-art linear programming solvers. This article describes an interdisciplinary approach to exploit the intrinsic structure of these large-scale linear problems to be able to solve them on massively parallel high-performance computers. A key aspect are extensions to the parallel interior-point solver PIPS-IPM originally developed for stochastic optimization problems. Furthermore, a newly developed GAMS interface to the solver as well as some GAMS language extensions to model block-structured problems will be described.
1438-0064
urn:nbn:de:0297-zib-66183
10.1007/978-3-319-89920-6_85
Operations Research Proceedings 2017
Thomas Breuer
Daniel Rehfeldt
Michael Bussieck
Karl-Kien Cao
Felix Cebulla
Frederik Fiand
Hans Christian Gils
Ambros Gleixner
Dmitry Khabi
Thorsten Koch
Daniel Rehfeldt
Manuel Wetzel
ZIB-Report
17-75
eng
uncontrolled
energy system models
eng
uncontrolled
interior-point methods
eng
uncontrolled
high-performance computing
Software
OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
Mathematical Optimization
Mathematical Optimization Methods
Gleixner, Ambros
Koch, Thorsten
Rehfeldt, Daniel
MODAL-SynLab
BEAM-ME
MODAL-Gesamt
https://opus4.kobv.de/opus4-zib/files/6618/zibreport.pdf