Abstract: I am author of many R packages and co-author of many others. This site lists my R packages with brief descriptions and links to the official CRAN releases as well as the development versions which are publicly available at GitHub.

R packages (main author)

grapherator (GitHub, CRAN)
The R package grapherator implements a modular approach to benachmark graph generation focusing on undirected, weighted graphs. The graph generation process follows a three-step procedure: placing nodes, connecting nodes and assigning weights. Each step can be repeated multiple times with different generator functions.
mcMST (GitHub, CRAN):
Package with mainly evolutionary algorithms and operators to tackle the multi-criteria minimum spanning tree problem.
smoof (GitHub, CRAN):
This package contains lots of single- and multi-objective test functions, which are widely used within the literature for benchmarking numerical optimization algorithms.
ecr (GitHub, CRAN):
Evolutionary Computation in R, is a package for evolutionary optimization in R. It is able to handle single-, as well as multi-objective functions. Aside from a lot of already implemented operators, the package allows to easily integrate own operators and representations.
netgen (GitHub, CRAN):
Methods for generating random or clustered networks in order to benchmark algorithms for combinatorial optimization problems on graphs, e.g. the Travelling-Salesperson-Problem (TSP) or the Vehicle-Routing-Problem (VRP). Furthermore, this package contains methods for morphing networks, importing from and exporting into the TSPlib format, as well as various visualization techniques.
salesperson (GitHub):
Comprehensive collection of functions for solving and analyzing the symmetric Traveling Salesperson Problem (TSP) by means of instance characteristics, frequently termed instance features.
acotsp (GitHub):
Ant Colony Optimization (ACO) algorithms for the Traveling Salesperson Problems (TSP).
cmaesr (GitHub, CRAN):
Implementation of the Covariance Matrix Adaption - Evolution Strategy (CMA-ES) and its restart variant IPOP-CMA-ES.

R packages (developer)

mlr (GitHub, CRAN):
Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized.
mlrMBO (GitHub, CRAN):
Framework for (sequential) model-based optimization. It offers methods to optimize numeric or discrete influence parameters of non-linear black-box single- or multi-objective target functions like an industrial simulator or a time-consuming algorithm using cheap surrogate models.
openml-r (GitHub, CRAN):
Interface to OpenML - an online machine learning platform where researchers can automatically log and share data, code, and experiments, and organize them online to work and collaborate more effectively. We provide a R interface to the OpenML API in order to download and upload data sets, tasks, flows and runs.
ParamHelpers (GitHub, CRAN):
Collection of helper functions for parameter descriptions and operations in black-box optimization, tuning and machine learning.
rcoco (GitHub)
R interface to the COCO (COmparing Continuous Optimisers) platform for systematic comparisons of real-parameter global optimisers written in R.
farff (GitHub, CRAN):
A faster parser for the arff file format.