Artikel
Solving polyhedral d.c. optimization problems via concave minimization
The problem of minimizing the difference of two convex functions is called polyhedral d.c. optimization problem if at least one of the two component functions is polyhedral. We characterize the existence of global optimal solutions of polyhedral d.c. optimization problems. This result is used to show that, whenever the existence of an optimal solution can be certified, polyhedral d.c. optimization problems can be solved by certain concave minimization algorithms. No further assumptions are necessary in case of the first component being polyhedral and just some mild assumptions to the first component are required for the case where the second component is polyhedral. In case of both component functions being polyhedral, we obtain a primal and dual existence test and a primal and dual solution procedure. Numerical examples are discussed.
- Language
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Englisch
- Bibliographic citation
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Journal: Journal of Global Optimization ; ISSN: 1573-2916 ; Volume: 78 ; Year: 2020 ; Issue: 1 ; Pages: 37-47 ; New York, NY: Springer US
- Classification
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Mathematik
Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation
Single Equation Models; Single Variables: Other
Social Economics‡
- Subject
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Global optimization
D.c. programming
Multi-objective linear programming
Linear vector optimization
- Event
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Geistige Schöpfung
- (who)
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vom Dahl, Simeon
Löhne, Andreas
- Event
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Veröffentlichung
- (who)
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Springer US
- (where)
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New York, NY
- (when)
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2020
- DOI
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doi:10.1007/s10898-020-00913-z
- Last update
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10.03.2025, 11:41 AM CET
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Object type
- Artikel
Associated
- vom Dahl, Simeon
- Löhne, Andreas
- Springer US
Time of origin
- 2020
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