Impossibility Results in AI: a survey

M Brcic, RV Yampolskiy - Acm computing surveys, 2023 - dl.acm.org
An impossibility theorem demonstrates that a particular problem or set of problems cannot
be solved as described in the claim. Such theorems put limits on what is possible to do …

Machine learning-based multi-objective optimization for efficient identification of crystal plasticity model parameters

K Veasna, Z Feng, Q Zhang, M Knezevic - Computer Methods in Applied …, 2023 - Elsevier
A set of constitutive model parameters along with crystallography governs the activation of
deformation mechanisms in crystal plasticity. The constitutive parameters are typically …

Distributed cooperative coevolution of data publishing privacy and transparency

YF Ge, E Bertino, H Wang, J Cao, Y Zhang - ACM Transactions on …, 2023 - dl.acm.org
Data transparency is beneficial to data participants' awareness, users' fairness, and
research work's reproducibility. However, when addressing transparency requirements, we …

A Q-Learning based NSGA-II for dynamic flexible job shop scheduling with limited transportation resources

R Chen, B Wu, H Wang, H Tong, F Yan - Swarm and Evolutionary …, 2024 - Elsevier
With the widespread adoption of intelligent transportation equipment such as AGVs in the
manufacturing field, the flexible job shop scheduling considering limited transportation …

Directional Queries: Making Top-k Queries More Effective in Discovering Relevant Results

P Ciaccia, D Martinenghi - Proceedings of the ACM on Management of …, 2024 - dl.acm.org
Top-k queries, in particular those based on a linear scoring function, are a common way to
extract relevant results from large datasets. Their major advantage over alternative …

[HTML][HTML] Optimal design of micro pumped-storage plants in the heart of a city

A Boroomandnia, B Rismanchi, W Wu… - Sustainable Cities and …, 2024 - Elsevier
Growth in renewable energy generation leads to an urgent need of expanding energy
storage capacity. While large pumped hydro storage remains the most established and …

[HTML][HTML] Enhancing the performance of hybrid wave-wind energy systems through a fast and adaptive chaotic multi-objective swarm optimisation method

M Neshat, NY Sergiienko, MM Nezhad, LSP da Silva… - Applied Energy, 2024 - Elsevier
Hybrid offshore renewable energy platforms have been proposed to optimise power
production and reduce the levelised cost of energy by integrating or co-locating several …

Surrogate-assisted environmental selection for fast hypervolume-based many-objective optimization

S Liu, H Wang, W Yao, W Peng - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Hypervolume (HV)-based evolutionary algorithms have been widely used to handle many-
objective optimization problems. In such algorithms, HV-based environmental selection …

A survey on Pareto front learning for multi-objective optimization

S Kang, K Li, R Wang - Journal of Membrane Computing, 2024 - Springer
Multi-objective optimization (MOO) is challenging since it needs to deal with multiple
conflicting objectives. Multi-objective evolutionary algorithms (MOEAs) are the mainstream …

Surrogate-based decision-making of community building portfolios under uncertain consequences and risk attitudes

GA Anwar, Y Dong - Engineering Structures, 2022 - Elsevier
The performance of community building portfolios under extreme events is increasingly
been assessed in terms of socioeconomic and environmental consequences. These …