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A New Method of Constrained Optimization and a Comparison With Other Methods
Abstract
A new method for finding the maximum of a general non-linear function of several variables within a constrained region is described, and shown to be efficient compared with existing methods when the required optimum lies on one or more constraints. The efficacy of using effective constraints to eliminate variables is demonstrated, and a program to achieve this easily and automatically is described. Finally, the performance of the new method (the “Complex” method) with unconstrained problems, is compared with those of the Simplex method, from which it was evolved, and Rosenbrock's method.
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Cited by
Jiang, J., Liu, S., Ma, Z., Wang, L. Y., & Wu, K. (2016) · Energy · doi:10.1016/j.energy.2016.10.087 · Cited by 47
Metadata
- Authors
- Box, M. J.
- Venue
- The Computer Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 1965-04-01
- Volume
- 8
- Issue
- 1
- Pages
- 42-52
- ISSN
- 0010-4620 (ISSN-L)
- 1460-2067
- OpenAlex
- W2163918103
- Cited by
- 1,302
- References
- 0
- FWCI
- 3.23
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A New Method of Constrained Optimization and a Comparison With Other Methods. https://app.cochat.ai/papers/10.1093/comjnl/8.1.42
- The paper
- Box, M. J. (1965). A New Method of Constrained Optimization and a Comparison With Other Methods. The Computer Journal. https://doi.org/10.1093/comjnl/8.1.42
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.
