Runtime analysis of the SMS-EMOA for many-objective optimization
W Zheng, B Doerr - Proceedings of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
The widely used multiobjective optimizer NSGA-II was recently proven to have considerable
difficulties in many-objective optimization. In contrast, experimental results in the literature …
difficulties in many-objective optimization. In contrast, experimental results in the literature …
A mathematical runtime analysis of the Non-dominated Sorting Genetic Algorithm III (NSGA-III)
S Wietheger, B Doerr - Proceedings of the Genetic and Evolutionary …, 2024 - dl.acm.org
The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is the most prominent multi-
objective evolutionary algorithm for real-world applications. While it performs evidently well …
objective evolutionary algorithm for real-world applications. While it performs evidently well …
Stochastic population update can provably be helpful in multi-objective evolutionary algorithms
Evolutionary algorithms (EAs) have been widely and successfully applied to solve multi-
objective optimization problems, due to their nature of population-based search. Population …
objective optimization problems, due to their nature of population-based search. Population …
The first proven performance guarantees for the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) on a combinatorial optimization problem
The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is one of the most prominent
algorithms to solve multi-objective optimization problems. Recently, the first mathematical …
algorithms to solve multi-objective optimization problems. Recently, the first mathematical …
Runtime analyses of NSGA-III on many-objective problems
NSGA-II and NSGA-III are two of the most popular evolutionary multi-objective algorithms
used in practice. While NSGA-II is used for few objectives such as 2 and 3, NSGA-III is …
used in practice. While NSGA-II is used for few objectives such as 2 and 3, NSGA-III is …
[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 …
objective evolutionary algorithm (MOEA) in real-world applications. However, in contrast to …
Towards running time analysis of interactive multi-objective evolutionary algorithms
T Lu, C Bian, C Qian - Proceedings of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
Evolutionary algorithms (EAs) are widely used for multi-objective optimization due to their
population-based nature. Traditional multi-objective EAs (MOEAs) generate a large set of …
population-based nature. Traditional multi-objective EAs (MOEAs) generate a large set of …
A first running time analysis of the Strength Pareto Evolutionary Algorithm 2 (SPEA2)
Evolutionary algorithms (EAs) have emerged as a predominant approach for addressing
multi-objective optimization problems. However, the theoretical foundation of multi-objective …
multi-objective optimization problems. However, the theoretical foundation of multi-objective …
Already moderate population sizes provably yield strong robustness to noise
Experience shows that typical evolutionary algorithms can cope well with stochastic
disturbances such as noisy function evaluations. In this first mathematical runtime analysis of …
disturbances such as noisy function evaluations. In this first mathematical runtime analysis of …
Illustrating the efficiency of popular evolutionary multi-objective algorithms using runtime analysis
Runtime analysis has recently been applied to popular evolutionary multi-objective (EMO)
algorithms like NSGA-II in order to establish a rigorous theoretical foundation. However …
algorithms like NSGA-II in order to establish a rigorous theoretical foundation. However …