Qualitative selection strategies in genetic-based evolutionary economic models

Autor:	V. Loia, S. Scandizzo
Rok vydání:	2002
Předmět:	Fuzzy clustering Fitness function business.industry Cultural algorithm Computer science Interactive evolutionary computation Machine learning computer.software_genre Genetic algorithm Artificial intelligence Genetic representation Cluster analysis business computer Selection (genetic algorithm)
Zdroj:	Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society.
Popis:	We use an evolutionary economic model based on a "genetic" representation of firm's behaviour which can naturally be implemented by means of a genetic algorithm. We suggest that both optimisation performance and simulation power may be enhanced incorporating in genetic algorithms a sophisticated fuzzy clustering algorithm. Such a system would be worth using in all those cases where uncertainty and imprecision occur in the evaluation of the fitness function, as well as in assessing similarities and differences among individuals.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::710e7954a27f28245cd6f75ea1edc5d3 https://doi.org/10.1109/isuma.1995.527717 Zobrazit plný text záznamu