Standard
A scenario-based approach for robust linear optimization. /
Goerigk, Marc; Schöbel, Anita.
Theory and Practice of Algorithms in (Computer) Systems. ed. / Alberto Marchetti-Spaccamela; Michael Segal. Berlin: Springer, 2011. p. 139-150 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6595).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Goerigk, M & Schöbel, A 2011,
A scenario-based approach for robust linear optimization. in A Marchetti-Spaccamela & M Segal (eds),
Theory and Practice of Algorithms in (Computer) Systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6595, Springer, Berlin, pp. 139-150, 1st International ICST Conference on Theory and Practice of Algorithms in (Computer) Systems, TAPAS 2011, Rome, Italy,
18/04/11.
https://doi.org/10.1007/978-3-642-19754-3_15
APA
Vancouver
Goerigk M, Schöbel A.
A scenario-based approach for robust linear optimization. In Marchetti-Spaccamela A, Segal M, editors, Theory and Practice of Algorithms in (Computer) Systems. Berlin: Springer. 2011. p. 139-150. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-19754-3_15
Author
Goerigk, Marc ; Schöbel, Anita. /
A scenario-based approach for robust linear optimization. Theory and Practice of Algorithms in (Computer) Systems. editor / Alberto Marchetti-Spaccamela ; Michael Segal. Berlin : Springer, 2011. pp. 139-150 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Bibtex
@inproceedings{4f6a41fe42144e13aac45a5dd6743ac5,
title = "A scenario-based approach for robust linear optimization",
abstract = "Finding robust solutions of an optimization problem is an important issue in practice. The established concept of Ben-Tal et al. [2] requires that a robust solution is feasible for all possible scenarios. However, this concept is very conservative and hence may lead to solutions with a bad objective value and is in many cases hard to solve. Thus it is not suitable for most practical applications. In this paper we suggest an algorithm for calculating robust solutions that is easy to implement and not as conservative as the strict robustness approach. We show some theoretical properties of our approach and evaluate it using linear programming problems from NetLib.",
keywords = "Algorithm Engineering, Linear Programming, Location Theory, Robust Optimization",
author = "Marc Goerigk and Anita Sch{\"o}bel",
year = "2011",
doi = "10.1007/978-3-642-19754-3_15",
language = "English",
isbn = "9783642197536",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "139--150",
editor = "Alberto Marchetti-Spaccamela and Michael Segal",
booktitle = "Theory and Practice of Algorithms in (Computer) Systems",
note = "1st International ICST Conference on Theory and Practice of Algorithms in (Computer) Systems, TAPAS 2011 ; Conference date: 18-04-2011 Through 20-04-2011",
}
RIS
TY - GEN
T1 - A scenario-based approach for robust linear optimization
AU - Goerigk, Marc
AU - Schöbel, Anita
PY - 2011
Y1 - 2011
N2 - Finding robust solutions of an optimization problem is an important issue in practice. The established concept of Ben-Tal et al. [2] requires that a robust solution is feasible for all possible scenarios. However, this concept is very conservative and hence may lead to solutions with a bad objective value and is in many cases hard to solve. Thus it is not suitable for most practical applications. In this paper we suggest an algorithm for calculating robust solutions that is easy to implement and not as conservative as the strict robustness approach. We show some theoretical properties of our approach and evaluate it using linear programming problems from NetLib.
AB - Finding robust solutions of an optimization problem is an important issue in practice. The established concept of Ben-Tal et al. [2] requires that a robust solution is feasible for all possible scenarios. However, this concept is very conservative and hence may lead to solutions with a bad objective value and is in many cases hard to solve. Thus it is not suitable for most practical applications. In this paper we suggest an algorithm for calculating robust solutions that is easy to implement and not as conservative as the strict robustness approach. We show some theoretical properties of our approach and evaluate it using linear programming problems from NetLib.
KW - Algorithm Engineering
KW - Linear Programming
KW - Location Theory
KW - Robust Optimization
U2 - 10.1007/978-3-642-19754-3_15
DO - 10.1007/978-3-642-19754-3_15
M3 - Conference contribution/Paper
AN - SCOPUS:79953834519
SN - 9783642197536
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 139
EP - 150
BT - Theory and Practice of Algorithms in (Computer) Systems
A2 - Marchetti-Spaccamela, Alberto
A2 - Segal, Michael
PB - Springer
CY - Berlin
T2 - 1st International ICST Conference on Theory and Practice of Algorithms in (Computer) Systems, TAPAS 2011
Y2 - 18 April 2011 through 20 April 2011
ER -
