Improving hyper-heuristic performance through feature transformation


Hyper-heuristics are powerful search methodologies that can adapt to different kinds of problems. One element of paramount importance, however, is the selection module that they incorporate. Traditional approaches define a set of features for characterizing a problem and, thus, define how to best solve it. However, some features may vary nonlinearly as the… (More)
DOI: 10.1109/CEC.2017.7969623


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