Criteria for well designed chromosome representation and genetic operators

• Autorzy: Arabas J.
• Języki publikacji: EN

Abstrakty

EN

This chapter postulates criteria for the proper choice of chromosome encoding and genetic operators. The criteria are given intuitively and exemplified. To formulate the criteria, a set of genotypes is presented as a metric space with the metric introduced by the mutation. Encoding is a mapping from the phe notype to the genotype space: the pruper transformation of metrics is a quality criterion for the encoding. Operator bias is defined with respect to the genotype metric.

Słowa kluczowe

EN

evolutionary computation; evolutionary algorithm; genetic operators; chromosome; genetics

PL

obliczenia ewolucyjne; algorytm ewolucyjny; operatory genetyczne; chromosom; genetyka

• Wydawca: Oficyna Wydawnicza Politechniki Warszawskiej
• Czasopismo: Prace Naukowe Politechniki Warszawskiej. Elektronika
• Rocznik: 2002
• Tom: z. 139
• Strony: 75--83
• Opis fizyczny: Bibliogr. 7 poz., tab.

Twórcy

autor

Arabas J.

• Warsaw University of Technology, Institute of Electronic Systems, ul. Nowowiejska 15/19, 00-665 Warszawa

Bibliografia

• 1. Back T.: Evolutionary algorithms in theory and practice, Oxford University Press, New York, 1996.
• 2. Back T., Fogel D., Michalewicz Z. (eds.): Handbook of evolutionary computation, Oxford University Press, New York, 1996.
• 3. Billingsley W.: Probability and measure, Addison-Wesley, New York, 1988.
• 4. Goldberg D.: Genetic algorithms in search, optimization and machine learning, Addison Wesley, New York, 1989.
• 5. Michalewicz Z.: Genetic algorithms + data structures = evolution programs, Springers, Berlin, 1992.
• 6. Obuchowicz A.: Remarks on Gaussian and Cauchy mutation, National Conference on Evolutionary computation and Global Optimization, 2001.
• 7. Wolpert D., MacReasy W.: No free lunch theorem for optimization, IEEE Transactions on Evolutionary Computation, vol. 1, 1997, 67-82.