SPOT (version 2.11.10)

funPowellS: funPowellS (No. 19, More No. 13)

Description

Powells 4-dim Test Function

Usage

funPowellS(x)

Arguments

x

matrix (dim 1x4) of points to evaluate with the function. Rows for points and columns for dimension.

Value

1-column matrix with resulting function values

References

More, J. J., Garbow, B. S., and Hillstrom, K. E. (1981). Testing unconstrained optimization software. Trond Steihaug and Sara Suleiman Global convergence and the Powell singular function ACM Transactions on Mathematical Software (TOMS), 7(1), 17-41. 10.1145/355934.355936 http://owos.gm.fh-koeln.de:8055/bartz/optimization-ait-master-2020/blob/master/Jupyter.d/Exercise-VIIa.ipynb http://bab10.bartzandbartz.de:8033/bartzbeielstein/bab-optimization-ait-master-2020/-/blob/master/Jupyter.d/01spotNutshell.ipynb https://www.mat.univie.ac.at/~neum/glopt/bounds.html

Powells Test function, M. J. D. Powell, 1962 An automatic method for finding the local minimum of a function. The Computer Journal, 3(3), 175-184. https://www.sfu.ca/~ssurjano/powell.html

Examples

# NOT RUN {
x1 <- matrix(c(0,0,0,0),1,)
funPowellS(x1)
x2 <- matrix(c(3,-1,0,1),1,)
funPowellS(x2)
x3 <- matrix(c(0,0,0,-2),1,)
funPowellS(x3)
# optimization run with SPOT and 15 evaluations
res_fun <- spot(,funPowellS,c(-4,-4,-4,-4 ),c(5,5,5,5),control=list(funEvals=15))
res_fun

# }