5 citations · 11 across the 5 of their papers we have counts for
5 papers
Clustering in Dynamic Environments: A Framework for Benchmark Dataset Generation With Heterogeneous Changes
Danial Yazdani, Juergen Branke, Mohammad Sadegh Khorshidi +4
Clustering in dynamic environments is of increasing importance, with broad applications ranging from real-time data analysis and online unsupervised learning to dynamic facility lo…
EDOLAB: An Open-Source Platform for Education and Experimentation with Evolutionary Dynamic Optimization Algorithms
Mai Peng, Delaram Yazdani, Zeneng She +9
Many real-world optimization problems exhibit dynamic characteristics, posing significant challenges for traditional optimization techniques. Evolutionary Dynamic Optimization Algo…
BOP-Elites, a Bayesian Optimisation Approach to Quality Diversity Search with Black-Box descriptor functions
Paul Kent, Adam Gaier, Jean-Baptiste Mouret +1
Quality Diversity (QD) algorithms such as MAP-Elites are a class of optimisation techniques that attempt to find many high performing points that all behave differently according t…
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks
George Watkins, Giovanni Montana, Juergen Branke
The graph colouring problem consists of assigning labels, or colours, to the vertices of a graph such that no two adjacent vertices share the same colour. In this work we investiga…
Performance Metrics for Multi-Objective Optimisation Algorithms Under Noise
Juergen Branke
This paper discusses the challenge when evaluating multi-objective optimisation algorithms under noise, and argues that decision maker preferences need to be taken into account. It…