Meta-Black-Box optimization for evolutionary algorithms: Review and perspective
Abstract Black-Box Optimization (BBO) is increasingly vital for addressing complex real-
world optimization challenges, where traditional methods fall short due to their reliance on …
world optimization challenges, where traditional methods fall short due to their reliance on …
Multi-agent dynamic algorithm configuration
Automated algorithm configuration relieves users from tedious, trial-and-error tuning tasks. A
popular algorithm configuration tuning paradigm is dynamic algorithm configuration (DAC) …
popular algorithm configuration tuning paradigm is dynamic algorithm configuration (DAC) …
A many-objective evolutionary algorithm with Pareto-adaptive reference points
We propose a new many-objective evolutionary algorithm with Pareto-adaptive reference
points. In this algorithm, the shape of the Pareto-optimal front (PF) is estimated based on a …
points. In this algorithm, the shape of the Pareto-optimal front (PF) is estimated based on a …
Reproducibility in evolutionary computation
Experimental studies are prevalent in Evolutionary Computation (EC), and concerns about
the reproducibility and replicability of such studies have increased in recent times, reflecting …
the reproducibility and replicability of such studies have increased in recent times, reflecting …
Benchmarking multi-and many-objective evolutionary algorithms under two optimization scenarios
Recently, a large number of multi-objective evolutionary algorithms (MOEAs) for many-
objective optimization problems have been proposed in the evolutionary computation …
objective optimization problems have been proposed in the evolutionary computation …
Constrained multiobjective optimization: Test problem construction and performance evaluations
Constrained multiobjective optimization abounds in practical applications and is gaining
growing attention in the evolutionary computation community. Artificial test problems are …
growing attention in the evolutionary computation community. Artificial test problems are …
[HTML][HTML] Efficiency of biradial impulse turbines concerning rotor blade angle, guide-vane deflection and blockage
DN Ferreira, LMC Gato, L Eça - Energy, 2023 - Elsevier
Self-rectifying impulse turbines have two sets of guide vanes symmetrically located on each
rotor side. Aerodynamic losses resulting from the inherent misalignment between the rotor …
rotor side. Aerodynamic losses resulting from the inherent misalignment between the rotor …
Dynamic variable analysis guided adaptive evolutionary multi-objective scheduling for large-scale workflows in cloud computing
Y **a, X Luo, W Yang, T **, J Li, L **ng… - Swarm and Evolutionary …, 2024 - Elsevier
Energy consumption and makespan of workflow execution are two core performance
indicators in operating cloud platforms. But, simultaneously optimizing these two indicators …
indicators in operating cloud platforms. But, simultaneously optimizing these two indicators …
An empirical investigation of the optimality and monotonicity properties of multiobjective archiving methods
M Li, X Yao - … Optimization: 10th International Conference, EMO 2019 …, 2019 - Springer
Most evolutionary multiobjective optimisation (EMO) algorithms explicitly or implicitly
maintain an archive for an approximation of the Pareto front. A question arising is whether …
maintain an archive for an approximation of the Pareto front. A question arising is whether …
Automatically designing state-of-the-art multi-and many-objective evolutionary algorithms
A recent comparison of well-established multiobjective evolutionary algorithms (MOEAs) has
helped better identify the current state-of-the-art by considering (i) parameter tuning through …
helped better identify the current state-of-the-art by considering (i) parameter tuning through …