simpleDE {adagio} R Documentation

## Simple Differential Evolution Algorithm

### Description

Simple Differential Evolution for Minimization.

### Usage

```simpleDE(fun, lower, upper, N = 64, nmax = 256, r = 0.4,
confined = TRUE, log = FALSE)
```

### Arguments

 `fun` the objective function to be minimized. `lower` vector of lower bounds for all coordinates. `upper` vector of upper bounds for all coordinates. `N` population size. `nmax` bound on the number of generations. `r` amplification factor. `confined` logical; stay confined within bounds. `log` logical; shall a trace be printed.

### Details

Evolutionary search to minimize a function: For points in the current generation, children are formed by taking a linear combination of parents, i.e., each member of the next generation has the form

p_1 + r(p_2 - p_3)

where the p_i are members of the current generation and r is an amplification factor.

### Value

List with the following components:

 `fmin` function value at the minimum found. `xmin` numeric vector representing the minimum. `nfeval` number of function calls.

### Note

Original Mathematica version by Dirk Laurie in the SIAM textbook. Translated to R by Hans W Borchers.

### Author(s)

HwB <hwborchers@googlemail.com>

### References

Dirk Laurie. “A Complex Optimization". Chapter 5 In: F. Bornemann, D. Laurie, S. Wagon, and J. Waldvogel (Eds.). The SIAM 100-Digit Challenge. Society of Industrial and Applied Mathematics, 2004.

### See Also

`simpleEA`, `DEoptim` in the ‘DEoptim’ package.

### Examples

```  simpleDE(fnTrefethen, lower = c(-1,-1), upper = c(1,1))
# \$fmin
#  -3.306869
# \$xmin
#  -0.02440308  0.21061243  # this is the true global optimum!
```

[Package adagio version 0.8.4 Index]