Each candidate proposes x + r1 (x_best - |x|) - r2 (x_worst - |x|), r1, r2
uniform per coordinate, and keeps it when better.
Usage
JayaAlgorithm(f, bounds, n_pop = 20, max_iter = 200, seed = 0)
Arguments
- f
Objective to minimise.
- bounds
List of c(low, high) pairs or a two-column matrix.
- n_pop
Population size.
- max_iter
Iterations.
- seed
Philox seed.
Value
list(x, fun, estimate, history, n_fev, method).
References
Rao, R. V. (2016). Jaya: a simple and new optimization algorithm
for solving constrained and unconstrained optimization problems.
International Journal of Industrial Engineering Computations 7, 19-34.
Examples
JayaAlgorithm(function(x) sum(x^2), list(c(-5, 5), c(-5, 5)), max_iter = 50)$fun
#> [1] 8.166247e-09
