An Experimental Study of Adaptive Control for Evolutionary Algorithms
This addresses a key issue in evolutionary computation for researchers and practitioners, but it appears incremental as it builds on existing control paradigms.
The paper tackled the problem of balancing exploration versus exploitation in evolutionary algorithms by using an adaptive controller for operator selection, resulting in improved solution quality.
The balance of exploration versus exploitation (EvE) is a key issue on evolutionary computation. In this paper we will investigate how an adaptive controller aimed to perform Operator Selection can be used to dynamically manage the EvE balance required by the search, showing that the search strategies determined by this control paradigm lead to an improvement of solution quality found by the evolutionary algorithm.