Handbook of Memetic Algorithms pp 73-94 | Cite as
Memetic Algorithms in Discrete Optimization
Chapter
Introduction
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 + .
Keywords
Local Search Candidate Solution Memetic Algorithm Discrete Optimization Local Search Algorithm
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© Springer-Verlag Berlin Heidelberg 2012