de_optimize: Differential Evolution Engine

In metANN: Metaheuristic and Gradient-Based Optimization for Neural Network Training and Continuous Problems

Differential Evolution Engine

Description

Internal implementation of Differential Evolution using the rand/1/bin strategy.

Usage

de_optimize(fn, lower, upper, optimizer, verbose = TRUE, ...)

Arguments

fn	Objective function.
lower	Numeric vector of lower bounds.
upper	Numeric vector of upper bounds.
optimizer	A DE optimizer object.
verbose	Logical. If TRUE, progress information is printed.
...	Additional arguments passed to fn.

Value

An object of class "met_optimize_result".

metANN documentation built on May 16, 2026, 1:06 a.m.