23 citations · 89 across the 19 of their papers we have counts for
5 papers · 1 filter
Analysis of modular CMA-ES on strict box-constrained problems in the SBOX-COST benchmarking suite
Diederick Vermetten, Manuel López-Ibáñez, Olaf Mersmann +2
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. Consequentl…
Are Evolutionary Algorithms Safe Optimizers?
Youngmin Kim, Richard Allmendinger, Manuel López-Ibáñez
We consider a type of constrained optimization problem, where the violation of a constraint leads to an irrevocable loss, such as breakage of a valuable experimental resource/platf…
SonOpt: Sonifying Bi-objective Population-Based Optimization Algorithms
Tasos Asonitis, Richard Allmendinger, Matt Benatan +1
We propose SonOpt, the first (open source) data sonification application for monitoring the progress of bi-objective population-based optimization algorithms during search, to faci…
Heterogeneous Objectives: State-of-the-Art and Future Research
Richard Allmendinger, Joshua Knowles
Multiobjective optimization problems with heterogeneous objectives are defined as those that possess significantly different types of objective function components (not just incomm…
HAWKS: Evolving Challenging Benchmark Sets for Cluster Analysis
Cameron Shand, Richard Allmendinger, Julia Handl +2
Comprehensive benchmarking of clustering algorithms is rendered difficult by two key factors: (i)~the elusiveness of a unique mathematical definition of this unsupervised learning…