We present IOHexperimenter, the experimentation module of the IOHprofiler project.
IOHexperimenter aims at providing an easy-to-use and customizable toolbox for …

Benchmarking heuristic algorithms is vital to understand under which conditions and on
what kind of problems certain algorithms perform well. In most current research into heuristic …

New contributions in the field of iterative optimisation heuristics are often made in an
iterative manner. Novel algorithmic ideas are not proposed in isolation, but usually as …

Extending a recent suggestion to generate new instances for numerical black-box
optimization benchmarking by interpolating pairs of the well-established BBOB functions …

Benchmarking plays a major role in the development and analysis of optimization
algorithms. As such, the way in which the used benchmark problems are defined …

Choosing a set of benchmark problems is often a key component of any empirical evaluation
of iterative optimization heuristics. In continuous, single-objective optimization, several sets …

Within the optimization community, the question of how to generate new optimization
problems has been gaining traction in recent years. Within topics such as instance space …

Solving real-world engineering optimization problems, such as automotive crashworthiness
optimization, is extremely challenging, because the problem characteristics are oftentimes …

The GKLS generator is one of the most used testbeds for benchmarking global optimization
algorithms. In this paper, we conduct both a computational analysis and the Exploratory …

Box-constraints limit the domain of decision variables and are common in real-world
optimization problems, for example, due to physical, natural or spatial limitations …