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The Computer Journal is a peer-reviewed journal published by Oxford University Press, covering Diverse Historical and Scientific Studies, History of Science and Medicine, Parallel Computing and Optimization Techniques.
| Publisher | Oxford University Press |
|---|---|
| Reference style | Author–year (OUP) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', The Computer Journal, 12(3), pp. 45–58.
Formats any DOI in the closest standard style — The Computer Journal has no published style definition, so this is an approximation. No sign-up. |
| Publishes research in | Diverse Historical and Scientific Studies History of Science and Medicine Parallel Computing and Optimization Techniques Academic and Historical Perspectives in Psychology Distributed and Parallel Computing Systems |
| ISSN | 0010-4620 |
| Citation impact (2-yr) | 1.65 |
| h-index | 143 |
| i10-index | 2,265 |
| Total citations | 192,539 |
| Article processing charge | $3,232 |
| Top institutions publishing here | Chinese Academy of Sciences |
| Journal website | comjnl.oxfordjournals.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
A method is described for the minimization of a function of n variables, which depends on the comparison of function values at the (n + 1) vertices of a general simplex, followed by the replacement of the vertex with the highest value by another point. The simplex adapts itself to the local landscape, and contracts…
A quadratically convergent gradient method for locating an unconstrained local minimum of a function of several variables is described. Particular advantages are its simplicity and its modest demands on storage, space for only three vectors being required. An ALGOL procedure is presented, and the paper includes a discussion of results obtained by its used on…
A simple variation of the well-known method of minimizing a function of several variables by changing one parameter at a time is described. This variation is such that when the procedure is applied to a quadratic form, it causes conjugate directions to be chosen, so the ultimate rate of convergence is fast when the method…
A powerful iterative descent method for finding a local minimum of a function of several variables is described. A number of theorems are proved to show that it always converges and that it converges rapidly. Numerical tests on a variety of functions confirm these theorems. The method has been used to solve a system of…
An approach to variable metric algorithms has been investigated in which the linear search sub-problem no longer becomes necessary. The property of quadratic termination has been replaced by one of monotonic convergence of the eigenvalues of the approximating matrix to the inverse hessian. A convex class of updating formulae which possess this property has been…
