Showing papers on "Evolutionary computation published in 1988"

Genetic algorithms in search, optimization, and machine learning

Abstract: From the Publisher: This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs No prior knowledge of GAs or genetics is assumed, and only a minimum of computer programming and mathematics background is required

Evolution algorithms in combinatorial optimization

Abstract: Evolution algorithms for combinatorial optimization have been proposed in the 70's. They did not have a major influence. With the availability of parallel computers, these algorithms will become more important. In this paper we discuss the dynamics of three different classes of evolution algorithms: network algorithms derived from the replicator equation, Darwinian algorithms and genetic algorithms inheriting genetic information. We present a new genetic algorithm which relies on intelligent evolution of individuals. With this algorithm, we have computed the best solution of a famous travelling salesman problem. The algorithm is inherently parallel and shows a superlinear speedup in multiprocessor systems.