The Simple Genetic Algorithm (SGA) is a classical form of genetic search. Viewing the SGA as a mathematical object, Michael D. Vose provides an introduction to what is known (i.e., proven) about the theory of the SGA. He also makes available algorithms for the computation of mathematical objects related to the SGA. Although he describes the SGA in terms of heuristic search, the book is not about search or optimization per se. Rather, the focus is on the SGA as an evolutionary system. The author intends the book also to serve as an outline for exploring topics in mathematics and computer science in a goal-oriented way.
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It might be simple, but it's not easy. Computer scientist Michael D. Vose takes a rigorous look at The Simple Genetic Algorithm and shows the state of our knowledge in a book appropriate for advanced undergraduates, graduate students, and professionals.
Vose has decided to approach his subject as a mathematical object, keeping his discussion to a minimum and relying on mathematical demonstrations of what has been proven about this powerful genetic search. This approach maximizes the book's utility for its scope of readers; since each chapter builds on the material before, it makes a good teaching tool, but it is still a useful reference as the indexing helps the professional find proofs quickly.
Covering the basics of random heuristic searching and the nature of the algorithm, the book moves on to computing, transient and asymptotic behavior, models, and schemata. Cutting all of the material down to the basic provable theorems is not, as Vose admits, without problems: any speculation beyond these stripped-down proofs is left to the imaginative reader. But the intrepid explorer couldn't ask for firmer ground from which to launch flights of discovery, and genetic computation currently offers the widest frontiers. --Rob Lightner
Michael D. Vose is Associate Professor in the Department of Computer Science, the University of Tennessee at Knoxville.
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