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 …
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
A set of constitutive model parameters along with crystallography governs the activation of
deformation mechanisms in crystal plasticity. The constitutive parameters are typically …
deformation mechanisms in crystal plasticity. The constitutive parameters are typically …
Distributed cooperative coevolution of data publishing privacy and transparency
Data transparency is beneficial to data participants' awareness, users' fairness, and
research work's reproducibility. However, when addressing transparency requirements, we …
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 …
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 …
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
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 …
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
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 …
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
Hypervolume (HV)-based evolutionary algorithms have been widely used to handle many-
objective optimization problems. In such algorithms, HV-based environmental selection …
objective optimization problems. In such algorithms, HV-based environmental selection …
A survey on Pareto front learning for multi-objective optimization
Multi-objective optimization (MOO) is challenging since it needs to deal with multiple
conflicting objectives. Multi-objective evolutionary algorithms (MOEAs) are the mainstream …
conflicting objectives. Multi-objective evolutionary algorithms (MOEAs) are the mainstream …
Surrogate-based decision-making of community building portfolios under uncertain consequences and risk attitudes
The performance of community building portfolios under extreme events is increasingly
been assessed in terms of socioeconomic and environmental consequences. These …
been assessed in terms of socioeconomic and environmental consequences. These …