37 citations · 58 across the 7 of their papers we have counts for
7 papers
Real-valued Evolutionary Multi-modal Multi-objective Optimization by Hill-Valley Clustering
S. C. Maree, T. Alderliesten, P. A. N. Bosman
In model-based evolutionary algorithms (EAs), the underlying search distribution is adapted to the problem at hand, for example based on dependencies between decision variables. Hi…
Multi-objective Optimization by Uncrowded Hypervolume Gradient Ascent
Timo M. Deist, Stefanus C. Maree, Tanja Alderliesten +1
Evolutionary algorithms (EAs) are the preferred method for solving black-box multi-objective optimization problems, but when gradients of the objective functions are available, it…
Ensuring smoothly navigable approximation sets by Bezier curve parameterizations in evolutionary bi-objective optimization -- applied to brachytherapy treatment planning for prostate cancer
S. C. Maree, T. Alderliesten, P. A. N. Bosman
The aim of bi-objective optimization is to obtain an approximation set of (near) Pareto optimal solutions. A decision maker then navigates this set to select a final desired soluti…
Uncrowded Hypervolume-based Multi-objective Optimization with Gene-pool Optimal Mixing
S. C. Maree, T. Alderliesten, P. A. N. Bosman
Domination-based multi-objective (MO) evolutionary algorithms (EAs) are today arguably the most frequently used type of MOEA. These methods however stagnate when the majority of th…
Benchmarking HillVallEA for the GECCO 2019 Competition on Multimodal Optimization
S. C. Maree, T. Alderliesten, P. A. N. Bosman
This report presents benchmarking results of the Hill-Valley Evolutionary Algorithm version 2019 (HillVallEA19) on the CEC2013 niching benchmark suite under the restrictions of the…
Real-Valued Evolutionary Multi-Modal Optimization driven by Hill-Valley Clustering
S. C. Maree, T. Alderliesten, D. Thierens +1
Model-based evolutionary algorithms (EAs) adapt an underlying search model to features of the problem at hand, such as the linkage between problem variables. The performance of EAs…