Abstract: In this study, we propose and develop a Machine Learning-based metasolver for the Multi-Agent Path Finding (MAPF) problem, with the aim of selecting the most suitable solver based on the ...
Abstract: This article devises a two-phase Kriging-assisted evolutionary algorithm (named TEA) to tackle expensive constrained multiobjective optimization problems (CMOPs). In the first phase, only ...
After a multi-year competition, the U.S. National Institute of Standards and Technology (NIST) selected a suite of algorithms ...
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