More than a decade after the first extensive overview on parameter control, we revisit the
field and present a survey of the state-of-the-art. We briefly summarize the development of …

Increasing cereal yield is needed to meet the projected increased demand for world food
supply of about 70% by 2050. Sirius, a process-based model for wheat, was used to …

Parameter tuning, that is, to find appropriate parameter settings (or configurations) of
algorithms so that their performance is optimized, is an important task in the development …

Metaheuristics are widely recognized as efficient approaches for many hard optimization
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …

This chapter pursues the insight that large language models (LLMs) trained to generate
code can vastly improve the effectiveness of mutation operators applied to programs in …

This e-book is devoted to global optimization algorithms, which are methods to find optimal
solutions for given problems. It especially focuses on Evolutionary Computation by …

Evolutionary algorithms (EAs) are robust stochastic optimisers that perform well over a wide
range of problems. Their robustness, however, may be affected by several adjustable …

Decomposition-based multiobjective evolutionary algorithms (MOEAs) decompose a
multiobjective optimization problem into a set of scalar objective subproblems and solve …

For genetic algorithms, new variants of the uniform crossover operator that introduce
selective pressure on the recombination stage are proposed. Operator probabilistic rates …

Background Protein-protein interactions are a pivotal component of many biological
processes and mediate a variety of functions. Knowing the tertiary structure of a protein …