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Monotonic Optimization: Problems and Solution Approaches
Abstract
Problems of maximizing or minimizing monotonic functions of n variables under monotonic constraints are discussed. A general framework for monotonic optimization is presented in which a key role is given to a property analogous to the separation property of convex sets. The approach is applicable to a wide class of optimization problems, including optimization problems dealing with functions representable as differences of increasing functions (d.i. functions).
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Cited by
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Shi, Y., Zhang, J., O'Donoghue, B., & Letaief, K. B. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2443731 · Cited by 118
Metadata
- Authors
- Tuy, H.
- Venue
- SIAM Journal on Optimization
- Published
- 2000-01
- Volume
- 11
- Issue
- 2
- Pages
- 464-494
- ISSN
- 1052-6234 (ISSN-L)
- 1095-7189
- OpenAlex
- W2066409766
- Cited by
- 311
- References
- 0
- FWCI
- 4.95
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Monotonic Optimization: Problems and Solution Approaches. https://app.cochat.ai/papers/10.1137/s1052623499359828
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- Tuy, H. (2000). Monotonic Optimization: Problems and Solution Approaches. SIAM Journal on Optimization. https://doi.org/10.1137/s1052623499359828
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
