The hypervolume indicator: Computational problems and algorithms

AP Guerreiro, CM Fonseca, L Paquete - ACM Computing Surveys …, 2021‏ - dl.acm.org
The hypervolume indicator is one of the most used set-quality indicators for the assessment
of stochastic multiobjective optimizers, as well as for selection in evolutionary multiobjective …

Differentiable expected hypervolume improvement for parallel multi-objective Bayesian optimization

S Daulton, M Balandat… - Advances in Neural …, 2020‏ - proceedings.neurips.cc
In many real-world scenarios, decision makers seek to efficiently optimize multiple
competing objectives in a sample-efficient fashion. Multi-objective Bayesian optimization …

A survey on the hypervolume indicator in evolutionary multiobjective optimization

K Shang, H Ishibuchi, L He… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
Hypervolume is widely used as a performance indicator in the field of evolutionary
multiobjective optimization (EMO). It is used not only for performance evaluation of EMO …

A first mathematical runtime analysis of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II)

W Zheng, Y Liu, B Doerr - Proceedings of the AAAI conference on …, 2022‏ - ojs.aaai.org
The non-dominated sorting genetic algorithm II (NSGA-II) is the most intensively used multi-
objective evolutionary algorithm (MOEA) in real-world applications. However, in contrast to …

A survey on recent progress in the theory of evolutionary algorithms for discrete optimization

B Doerr, F Neumann - ACM Transactions on Evolutionary Learning and …, 2021‏ - dl.acm.org
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 …

Stochastic population update can provably be helpful in multi-objective evolutionary algorithms

C Bian, Y Zhou, M Li, C Qian - Artificial Intelligence, 2025‏ - Elsevier
Evolutionary algorithms (EAs) have been widely and successfully applied to solve multi-
objective optimization problems, due to their nature of population-based search. Population …

Better running time of the non-dominated sorting genetic algorithm II (NSGA-II) by using stochastic tournament selection

C Bian, C Qian - International Conference on Parallel Problem Solving …, 2022‏ - Springer
Evolutionary algorithms (EAs) have been widely used to solve multi-objective optimization
problems, and have become the most popular tool. However, the theoretical foundation of …

[HTML][HTML] Mathematical runtime analysis for the non-dominated sorting genetic algorithm II (NSGA-II)

W Zheng, B Doerr - Artificial Intelligence, 2023‏ - Elsevier
The non-dominated sorting genetic algorithm II (NSGA-II) is the most intensively used multi-
objective evolutionary algorithm (MOEA) in real-world applications. However, in contrast to …

The hypervolume indicator: Problems and algorithms

AP Guerreiro, CM Fonseca, L Paquete - arxiv preprint arxiv:2005.00515, 2020‏ - arxiv.org
The hypervolume indicator is one of the most used set-quality indicators for the assessment
of stochastic multiobjective optimizers, as well as for selection in evolutionary multiobjective …

Pareto optimization for subset selection with dynamic cost constraints

V Roostapour, A Neumann, F Neumann, T Friedrich - Artificial Intelligence, 2022‏ - Elsevier
We consider the subset selection problem for function f with constraint bound B that changes
over time. Within the area of submodular optimization, various greedy approaches are …