Discrete optimization concerns in essence the search for a "best" configuration (optimal solution) among a set of finite candidate configurations according to a particular criterion. There are several ways to describe a discrete optimization problem. In its most general form, it can be defined as a collection of problem instances, each being specified by a pair (S,f) [704], where S is the set of finite candidate configurations, defining the search space; f is the cost or objective function, given by a mapping f: S→R +. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Hao, J. K. (2012). Memetic algorithms in discrete optimization. Studies in Computational Intelligence, 379, 73–94. https://doi.org/10.1007/978-3-642-23247-3_6
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