Niching mechanisms in evolutionary computations
Zdzisław Kowalczuk; Tomasz Białaszewski
International Journal of Applied Mathematics and Computer Science (2006)
- Volume: 16, Issue: 1, page 59-84
- ISSN: 1641-876X
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top- Brogan W.L. (1991): Modern Control Theory. - Englewood Cliffs, NJ: Prentice Hall. Zbl0747.93001
- Chen J., Patton R.J. and Liu G. (1996): Optimal residual design for fault diagnosis using multi-objective optimization and genetic algorithms. - Int. J. Syst. Sci., Vol. 27, No. 6, pp. 567-576. Zbl0854.93134
- Chambers L. (Ed.) (1995): Practical Handbook of Genetic Algorithms. - Boca Raton, FL: CRC Press. Zbl0840.68001
- Coello C.C.A. (2001): A short tutorial on evolutionary multiobjective optimization. - Proc. 1st Int. Conf. Evolutionary Multi-Criterion Optimization, Lecture Notes in Computer Science, No. 1993, pp. 21-40, Berlin: Springer.
- Cotta C. and Schaefer R. (Eds.) (2004): Evolutionary Computation. - Int. J. Appl. Math. Comput. Sci., Vol. 14, No. 3, pp. 279-440.
- Deb K., Pratap A., Argarwal S. and Meyarivan T. (2000): A fast and elitist multi-objective genetic algorithm: NSGA-II. - Techn. Rep., No. 200001 (PIN 208 016), Kanpur, India: Kanpur Genetic Algorithms Laboratory.
- De Jong K.A. (1975): An analysis of the behavior of a class of genetic adaptive systems. - Ph.D. thesis., Ann Arbor, MI: University of Michigan.
- Dridi M. and Kacem I. (2004): A hybrid approach for scheduling transportation networks. - Int. J. Appl. Math. Comput. Sci., Vol. 14, No. 3, pp. 397-409. Zbl1137.90331
- Fogarty T.C. and Bull L. (1995): Optimizing individual control rules and multiple communicating rule-based control systems with parallel distributed genetic algorithms. - IEE Proc. Contr. Theory Applic., Vol. 142, No. 3, pp. 211-215.
- Fonseca C.M. and Fleming P.J. (1993): Genetic algorithms for multi-objective optimization: Formulation, discussion and modification. - In: (Forrest, 1993), pp. 416-423.
- Forrest S. (Ed.) (1993): Genetic Algorithms. - Proc. 5th Int. Conf., San Mateo, CA: Morgan Kaufmann.
- Goldberg D.E. (1986): The genetic algorithm approach: Why, how, and what next. In: Adaptive and Learning Systems. Theory and Applications (K.S. Narendra, Ed.). - New York: Plenum Press, pp. 247-253.
- Goldberg D.E. (1989): Genetic Algorithms in Search, Optimization and Machine Learning. - Reading, MA: Addison-Wesley. Zbl0721.68056
- Goldberg D.E. (1990): Real-coded genetic algorithms, virtual alphabets, and blocking. - Techn. Rep., No. 90001, Champaing, IL: University of Illinois at Urbana. Zbl0764.68143
- Grefenstette J.J. (Ed.) (1985): Genetic Algorithms and their Applications. - Proc. Int. Conf., Pittsburgh, PA: Lawrence Erlbaum Associates.
- Hajela P. and Lin C.-Y. (1992): Genetic search strategies in multicriterion optimal design. - Struct. Optim., Vol. 4, No. 2, pp. 99-107.
- Holland H. (1975): Adaptation in Natural and Artificial Systems. - Ann Arbor, MI: University of Michigan Press.
- Horn J. and Nafpliotis N. (1993): Multiobjective optimization using the niched Pareto genetic algorithm. - Techn. Rep., No. 93005, Genetic Algorithms Laboratory, University of Illinois at Urbana.
- Horn J., Nafpliotis N. and Goldberg D.E. (1994): A niched Pareto genetic algorithm for multiobjective optimization. - Proc. 1st IEEE Conf. Evolutionary Computation, IEEE World Congress Computational Computation, Piscataway, NJ, Vol. 1, pp. 82-87.
- Huang Y. and Wang S. (1997): The identification of fuzzy grey prediction systems by genetic algorithms. - Int. J. Syst. Sci., Vol. 28, No. 1, pp. 15-24. Zbl0875.93234
- Izadi-Zamanabadi R. and Blanke M. (1998): A ship propulsion system model for fault-tolerant control. - Techn. Rep., No. 4262, Aalborg University, Denmark. Zbl0929.93005
- Kirstinsson K. (1992): System identification and control using genetic algorithms. - IEEE Trans. Syst. Man Cybern., Vol. 22, No. 5, pp. 1033-1046. Zbl0825.93940
- Korbicz J., Kościelny J.M., Kowalczuk Z. and Cholewa W., (Eds.) (2004): Fault Diagnosis. Models, Artificial Intelligence, Applications. - Berlin: Springer. Zbl1074.93004
- Kowalczuk Z. and Białaszewski T. (2000a): Pareto-optimal observers for ship propulsion systems by evolutionary algorithms. - Proc. IFAC Symp. Safeprocess, Budapest, Hungary, Vol. 2, pp. 914-919.
- Kowalczuk Z. and Białaszewski T. (2000b): Fitness and ranking individuals warped by niching mechanism. - Proc. Polish-German Symp. Science, Research, Education, Zielona Gora, Poland, pp. 97-102.
- Kowalczuk Z. and Białaszewski T. (2001): Evolutionary multi-objective optimization with genetic sex recognition. - Proc. 7th IEEE Int. Conf. Methods and Models in Automation and Robotics, Międzyzdroje, Poland, Vol. 1, pp. 143-148.
- Kowalczuk Z. and Białaszewski T. (2002): Performance and robustness design of control systems via genetic gender multi-objective optimization. - Proc. 15th IFAC World Congress, Barcelona, Spain, (CD-ROM, 2a).
- Kowalczuk Z. and Białaszewski T. (2003): Multi-gender genetic optimization of diagnostic observers. - Proc. IFAC Workshop Control Applications of Optimization, Visegrad, Hungary, pp. 15-20.
- Kowalczuk Z. and Białaszewski T. (2004a): Genetic algorithms in multi-objective optimization of detection observers. - In: (Korbicz et al., 2004), pp. 511-556.
- Kowalczuk Z. and Białaszewski T. (2004b): Periodic and continuous niching in genetic optimization of detection observers. - Proc. 10-th IEEE Int. Conf. Methods and Models in Automation and Robotics, Międzyzdroje, Poland, Vol. 1, pp. 781-786.
- Kowalczuk Z., Suchomski P. and Białaszewski T. (1999a): Evolutionary multi-objective Pareto optimization of diagnostic state observers. - Int. J. Appl. Math. Comput. Sci., Vol. 9, No. 3, pp. 689-709. Zbl0945.93515
- Kowalczuk Z., Suchomski P. and Białaszewski T. (1999b): Genetic multi-objective Pareto optimization of state observers for FDI. - Proc. Europ. Contr. Conf., Karlsruhe, Germany, (CD-ROM, CP-15:10). Zbl0945.93515
- Kowalczuk Z. and Suchomski P. (2004a): Control theory methods in diagnostic system design. In: (Korbicz et al., 2004), pp. 155-218.
- Kowalczuk Z. and Suchomski P. (2004b): Optimal detection observers based on eigenstructure assignment. In: (Korbicz et al., 2004), pp. 219-259.
- Li C.J., Tzeng T. and Jeon Y.C. (1997): A learning controller based on nonlinear ARX inverse model identified by genetic algorithm. - Int. J. Syst. Sci., Vol. 28, No. 8, pp. 847-855. Zbl0875.93083
- Linkens D.A. and Nyongensa H.O. (1995): Genetic algorithms for fuzzy control, Part 1: Offline system development and application. - IEE Proc. Contr. Theory Applic., Vol. 142, No. 3, pp. 161-185.
- Man K.S., Tang K.S., Kwong S. and Lang W.A.H. (1997): Genetic Algorithms for Control and Signal Processing. - London: Springer.
- Martinez M., Senent J. and Blacso X. (1996): A comparative study of classical vs. genetic algorithm optimization applied in GPC controller. - Proc. IFAC 13th Triennial Word Congress, San Francisco, CA, pp. 327-332.
- Michalewicz Z. (1996): Genetic Algorithms + Data Structures = Evolution Programs. - Berlin: Springer. Zbl0841.68047
- Obuchowicz A. and Pretki P. (2004): Phenotypic evolution with mutation based on symmetric, α-stable distributions. - Int. J. Appl. Math. Comput. Sci., Vol. 14, No. 3, pp. 289-316. Zbl1104.68566
- Park D. and Kandel A. (1994): Genetic-based new fuzzy reasoning models with application to fuzzy control. - IEEE Trans. Syst., Man Cybern., Vol. 24, No. 1, pp. 39-47.
- Patton R.J., Frank P.M. and Clark R.N., (Eds.) (1989): Fault Diagnosisin Dynamic Systems. Theory and Application. - New York: Prentice Hall.
- Ryan C. (1995): Niche and species formation in genetic algorithms, In: (Chambers, 1995). - Vol. 1, No. 2, pp. 55-74.
- Schaffer J.D. (1985): Multiple objective optimization with vector evaluated genetic algorithms. In: (Grefenstette, 1985). - pp. 93-100.
- Silverman B.W. (1986): Density Estimation for Statistics and Data Analysis. - London: Chapman and Hall. Zbl0617.62042
- Srinivas N. and Deb K. (1994): Multiobjective optimization using nondominated sorting in genetic algorithms. - Evolut. Comput., Vol. 2, No. 3, pp. 221-248.
- Suchomski P. and Kowalczuk Z. (2004): Robust H^∞-optimal synthesis of FDI systems, In: (Korbicz et al., 2004), pp. 261-298.
- Viennet R., Fontiex C. and Marc I. (1996): Multicriteria optimisation using a genetic algorithm for determining a Pareto set. - Int. J. Syst. Sci., Vol. 27, No. 2, pp. 255-260. Zbl0844.90079
- Zakian V. and Al-Naib U. (1973): Design of dynamical and control systems by the method of inequalities. - IEE Proc. Contr. Theory Applic., Vol. 120, No. 11, pp. 1421-1427.
- Zitzler E. and Thiele L. (1998): An evolutionary algorithm for multiobjective optimization: The Strength Pareto Evolutionary Algorithm. - Techn. Rep., No. 43, Zurich, Switzerland: Computer Engineering and Networks Laboratory, ETH.
- Zitzler E., Laumanns M. and Thiele L. (2001): SPEA-2: Improving the strength Pareto evolutionary algorithm. - Techn. Rep., No. 103, Zurich, Switzerland: Computer Engineering and Networks Laboratory, Dept. of Electrical Engineering, ETH.
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