Qualitative selection strategies in genetic-based evolutionary economic models

Author

Loia, Vincenzo ; Scandizzo, Sergio

Author_Institution

Dipartimento di Inf. ed Applicazioni, Salerno Univ., Italy

fYear

1995

Firstpage

333

Lastpage

338

Abstract

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

Keywords

commerce; corporate modelling; economic cybernetics; economics; fuzzy set theory; genetic algorithms; fitness function; genetic-based evolutionary economic models; imprecision; optimisation performance; qualitative selection strategies; simulation power; sophisticated fuzzy clustering algorithm; uncertainty; Artificial neural networks; Clustering algorithms; Environmental economics; Evolution (biology); Genetic algorithms; Laboratories; Power generation economics; Power system economics; Power system modeling; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Uncertainty Modeling and Analysis, 1995, and Annual Conference of the North American Fuzzy Information Processing Society. Proceedings of ISUMA - NAFIPS '95., Third International Symposium on

Conference_Location

College Park, MD

Print_ISBN

0-8186-7126-2

Type

conf

DOI

10.1109/ISUMA.1995.527717

Filename

527717