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Reworking the Standard Model of Competitive Markets: The Role of Fuzzy Logic and Genetic Algorithms in Modelling Complex Non-Linear Economic System AgEcon
Smith, Peter.
Some aspects of economic systems (eg, nonlinearity, qualitative variables) are intractable when incorporated into models. The widespread practice of excluding them (or greatly limiting their role) produces deviations of unknown size and form between the resulting models and the reality they purport to represent. To explore this issue, and the extent to which a change in methodology can improve tractability, a combination of two techniques, fuzzy logic and genetic algorithms, was applied to the problem of how the sellers in a freely competitive market, if initially trading at different prices, can find their way to supply/demand equilibrium. A multi-agent model was used to simulate the evolution of autonomously- learnt rule-governed behaviour, (i), under...
Tipo: Working or Discussion Paper Palavras-chave: Competition; Markets; Walrasian Crier; Equilibrium; Fuzzy logic; Genetic algorithms; Evolutionary algorithms; Industrial Organization.
Ano: 2004 URL: http://purl.umn.edu/30569
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Optimum contribution selection using differential evolution R. Bras. Zootec.
Carvalheiro,Roberto; Queiroz,Sandra Aidar de; Kinghorn,Brian.
A program to determine optimum contribution selection using differential evolution was developed. The objective function to be optimized was composed by the expected merit of the future progeny and the coancestry among selected parents. Simulated and real datasets of populations with overlapping generations were used to validate and test the performance of the program. The program was computationally efficient and feasible for practical applications. The expected consequences of using the program, in contrast to empirical procedures to control inbreeding and/or to selection based exclusively on expected genetic merit, would be the improvement of the selection response and a more effective control of inbreeding.
Tipo: Info:eu-repo/semantics/article Palavras-chave: Evolutionary algorithms; Genetic response; Inbreeding; Optimization; Selection.
Ano: 2010 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982010000700005
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