The theory of evolutionary computation for discrete search spaces has made significant
progress since the early 2010s. This survey summarizes some of the most important recent …

Abstract The Dynamic Vehicle Routing Problem (DVRP) is a complex variation of classical
Vehicle Routing Problem (VRP). The aim of DVRP is to find a set of routes to serve multiple …

In classical runtime analysis it has been observed that certain working principles of an
evolutionary algorithm cannot be understood by only looking at the asymptotic order of the …

Apart from few exceptions, the mathematical runtime analysis of evolutionary algorithms is
mostly concerned with expected runtimes, occasionally augmented by tail bounds. In this …

In single-objective optimization, it is well known that evolutionary algorithms also without
further adjustments can tolerate a certain amount of noise in the evaluation of the objective …

Real-world optimisation often involves uncertainty. Previous studies proved that evolutionary
algorithms (EAs) can be robust to noise when using proper parameter settings, including the …

We study evolutionary algorithms in a dynamic setting, where for each generation a different
fitness function is chosen, and selection is performed with respect to the current fitness …

In dynamic optimization problems, although the problem environments keep changing, a
new environment is usually related to its previous environments. Based on the relevance …

We analyse the performance of well-known evolutionary algorithms, the (1+ 1)(1+ 1) EA and
the (1+ λ)(1+ λ) EA, in the prior noise model, where in each fitness evaluation the search …

Many real-world optimization problems occur in environments that change dynamically or
involve stochastic components. Evolutionary algorithms and other bio-inspired algorithms …