Genetic Algorithms as Optimalisation Procedures
Keywords:
Genetic Algorithms, Optimalisation ProceduresAbstract
Drawing a parallel between biological and economic evolution provides an opportunity for the description of dynamic economic
processes changing in time by using genetic algorithms. The first step in finding algorithms in biological and economic processes is
to draw a parallel between the terms used in both disciplines and to determine the degree of elaboration of analogues. On the basis
of these ideas it can be stated that most biological terms can be used both in economics and in the social field, which satisfies the
essential condition for successful modeling.
Genetic algorithms are derived on the basis of Darwin-type biological evolution and the process starts from a possible state
(population), in most cases chosen at random. New generations emerge from this starting generation on the basis of various
procedures. These generating procedures go on until the best solution to the problem is found. Selection, recombination and
mutation are the most important genetic procedures.
References
ÁLMOS, A. ; GYRY, S. ; HORVÁTH, G. ; VÁRKONYINÉ KÓCZY, A. (2002): Genetikus algoritmusok, Budapest, Typotex Kiadó
ARIFOVIC, J. (1994): Genetic Algorithm Learning and the Cobweb-Modell, in: Journal of Economic Dynamic and Control, 18/1994, 3-28.
ARIFOVIC, J. (1998): Inflationary deficit financing in an Open Economy: Evolutionary Dynamics, Santa Fe Working Paper 99-05-038E.
BIRCHENHALL, C. (1995): Modular Technical Change and Genetic Algorithms, In: Computational Economics, 8/1995, 233-253.
BIRCHENHALL, C. KASTRINOS, N. METCALFE, S. (1997): Genetic algorithms in evolutionary modelling, In: Evolutionary Economics, 7/1997, 375-393.
BRENNER, T. (1998): Can evolutionary algorithms describe learning processes? In: Journal of Evolutionary Economics, 8/1998, 271-283.
DAWID, H. (1997): On the Convergence of Genetic Learning in a Double Auction Market, University of Vienna: POM working paper 6/1997.
KARAJZ, S. (2002): Genetikai algoritmusok a közgazdaságtani modellezésben, Doktoranduszok Fóruma, Miskolci Egyetem, Gazdaságtudományi Kar Szekciókiadványa, Miskolc, 2002. november 6., 21-24.
LAWRENZ, C. (1999): Rationale Erwartungen als Ergebnis eines evolutionären Prozesses? Lernen mit genetischen Algorithmen. Jena: Arbeitspapier für den 4. Doktoranden- und Habilitanden-Workshop „Evolutorische Ökonomik” in Buchenbach, 12.-15.05. 1999. Max-Planck-Institut zur Erforschung von Wirtschaftssystemen.
RIECHMANN, T. (1999): Learning and behavioral stability: An economic interpretaton of genetic algorithms, In: Journal of Evolutionary Economics, 9/1999, 225-242.
