This article presents the second Part of a two-Part survey that reviews evolutionary dynamic
optimization (EDO) for single-objective unconstrained continuous problems over the last two …

This paper provides a survey of the research done on optimization in dynamic environments
over the past decade. We show an analysis of the most commonly used problems, methods …

We study the problem of performing a sequence of optimal interventions in a dynamic causal
system where both the target variable of interest, and the inputs, evolve over time. This …

Many practical, real-world applications have dynamic features. If the changes in the fitness
function of an optimization problem are moderate, a complete restart of the optimization …

Optimization problems have attracted attention of researchers for decades. Commonly,
problem related data and problem domain are assumed to be exactly known beforehand …

We propose practical extensions to Bayesian optimization for solving dynamic problems. We
model dynamic objective functions using spatiotemporal Gaussian process priors which …

Self-adaptation is a popular parameter control technique in evolutionary computation, which
has been extensively studied in stationary optimisation. In the context of dynamic …

Particle swarm optimization has been successfully applied in many research and application
areas because of its effectiveness and easy implementation. In this work we extend one of …

The present work proposes a simple but effective self-adaptive strategy to control the
behaviour of a differential evolution (DE) based multipopulation algorithm for dynamic …

This paper is derived from an interest in the development of approaches to tackle dynamic
optimisation problems. This is a very challenging research area due to the fact that any …