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DOEoptimizer is a package that implements four optimization algorithms specifically designed for optimizing design of physical experiments criteria (a matrix input function).

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DOEoptimizer

DOEoptimizer is an R package that provides four optimization algorithms specifically designed to optimize criteria (matrix input functions) for physical experiments.
It offers a comprehensive set of tools and utilities for constructing optimal experimental designs using various optimization techniques, including genetic algorithms, simulated annealing, stochastic optimization, and greedy algorithms.

Installation

You can install the latest version of the package manually or directly from GitHub.

Option 1: Install from GitHub (Recommended)

Make sure you have the devtools package installed, then use:

install.packages("devtools")
devtools::install_github("TheseAdama/DOEoptimizer")

Option 2: Manual Installation (Download & Install ZIP)

  1. Download the ZIP or TAR.GZ file

    Download the latest version of the package in ZIP or TAR.GZ format.

    • For Windows: DOEoptimizer_x.y.z.zip
    • For Linux/macOS: DOEoptimizer_x.y.z.tar.gz
  2. Install the package manually in R

    Open your R session and run one of the following commands, replacing the file path with where you downloaded the archive:

    • On Windows:

      install.packages("path/to/DOEoptimizer_x.y.z.zip", repos = NULL, type = "win.binary")
    • On Linux/macOS:

      install.packages("path/to/DOEoptimizer_x.y.z.tar.gz", repos = NULL, type = "source")

After installation, load the package:

library(DOEoptimizer)

About

DOEoptimizer is a package that implements four optimization algorithms specifically designed for optimizing design of physical experiments criteria (a matrix input function).

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