Abstract
The goal of this chapter is to provide a simple introduction into the kind of genetic algorithms applied in economic theory. The main focus will be on technical aspects, the economic example merely serves as an illustration. This means that in this chapter new economic results will hardly be found. The model shown here is very simple and, more than this, it lacks one of the most important characteristics of the models to be presented in the further course of this work: It does not include state dependency of individual economic success1. The large number of simplifications make the model look a little stylized. Nevertheless, the simplifications are intentionally introduced in favor of clarity of the main technical goal, the introduction into the basic techniques of modeling economic problems in form of a genetic algorithm.
The characteristic of state dependency will, later on (Sects. 4.3 and 7.2.1), become the defining characteristic of economic GAs as opposed to technical GAs. This means that the model in this chapter, although having some economic contents, is not an economic GA in the sense of the above definition. There are many more GAs dealing with economic questions which are not economic GAs, like e.g. the famous Traveling Salesman problem (Michalewicz, 1996)
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© 2001 Springer-Verlag Berlin Heidelberg
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Riechmann, T. (2001). An Exemplary Introduction to Structure and Application of Genetic Algorithms in Economic Research. In: Learning in Economics. Contributions to Economics. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57612-6_3
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DOI: https://doi.org/10.1007/978-3-642-57612-6_3
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1384-5
Online ISBN: 978-3-642-57612-6
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