"Evolutionäre Algorithmen - Verfahren, Operatoren, Hinweise aus der Praxis"

Hartmut Pohlheim
Berlin, Heidelberg, New York: Springer-Verlag
322 Seiten, 105 Abbildungen und Tabellen
mit Matlab-Toolbox auf CD-ROM (GEATbx 1.95, Vollversion)

ISBN 3-540-66413-0 (erschienen: Oktober 1999)
Preis: DM 98,- DM
www.pohlheim.com/eavoh/

Literaturverzeichnis
(Evolutionäre Algorithmen)

Evolutionäre Algorithmen und Optimierung

[Ack87]
Ackley, D. H.: A connectionist machine for genetic hillclimbing. Boston: Kluwer Academic Publishers, 1987.

[Ack93]
Ackermann, J.: Robuste Regelung. Berlin, Heidelberg, New York: Springer-Verlag, 1993.

[AISB96]
Fogarty, T. C.: Evolutionary Computing. Proceedings of AISB Workshop on Evolutionary Computing 1996, Vol. 1143 of Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer-Verlag, 1996.

[AGP94]
Kinnear, K. E.: Advances in Genetic Programming. Cambridge: MIT Press, 1994.

[AGP96]
Angeline, P. J. and Kinnear, K. E.: Advances in Genetic Programming II. Cambridge: MIT Press, 1996.

[AGP99]
Spector, L., Langdon, W., O'Reilly, U.-M. and Angeline, P. J. (eds.): Advances in Genetic Programming III. Cambridge: MIT Press, 1999.

[Bäc96]
Bäck, T.: Evolutionary Algorithms in Theory and Practice - Evolution Strategies, Evolutionary Programming, Genetic Algorithms. New York, Oxford: Oxford University Press, 1996.
http://www.oup-usa.org/docs/0195099710.html

[BH91]
Bäck, T. and Hoffmeister, F.: Extended Selection Mechanisms in Genetic Algorithms. In [ICGA4], pp. 92-99, 1991.

[BS96]
Bäck, T. and Schütz, M.: Intelligent Mutation Rate Control in Canonical Genetic Algorithms. In Ras, Z. W. and Michalewicz, M.: Foundation of Intelligent Systems. 9th International Symposium, ISMIS '96, pp. 158-167, Berlin: Springer-Verlag, 1996.
http://lumpi.informatik.uni-dortmund.de/people/baeck/papers/ismis.ps.Z

[Bak85]
Baker, J. E.: Adaptive Selection Methods for Genetic Algorithms. In [ICGA1], pp. 101-111, 1985.

[Bak87]
Baker, J. E.: Reducing Bias and Inefficiency in the Selection Algorithm. In [ICGA2], pp. 14-21, 1987.

[Bal94]
Baluja, S.: Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning. Technical Report CMU-CS-94-163, Pittsburgh, Pennsylvania: School of Computer Science, Carnegie Mellon University, 1994.
ftp://reports.adm.cs.cmu.edu/1994/CMU-CS-94-163.ps

[Bey95]
Beyer, H.-G.: Toward a Theory of Evolution Strategies: On the Benefits of Sex - the (_/_,_) Theory. Evolutionary Computation, 3(1), pp. 81-111, 1995.

[BT95]
Blickle, T. and Thiele, L.: A Comparison of Selection Schemes used in Genetic Algorithms (2. Edition). TIK Report No. 11, Computer Engineering and Communication Networks Lab (TIK), Swiss Federal Institute of Technology (ETH) Zürich, Switzerland, 1995.
http://www.tik.ee.ethz.ch/Publications/TIK-Reports/TIK-Report11abstract.html

[BEL95]
Böcker, J, Endrikat, C. and Liu, S.: A Systematic Approach to State Feedback Controller Design for DC/DC Line-Side Traction Converters. Proc. EPE'95, Sevilla, Vol. 1, pp. 314-318, 1995.

[BW96]
Böcker, J. and Wu, Z.: Symmetry Properties of Multi-Variable Control Systems. Technical Note, 25/96, Daimler Benz AG, 1996.

[Boo87]
Booker, L.: Improving search in genetic algorithms. In [Dav87], pp. 61-73, 1987.

[Box57]
Box, G. E. P.: Evolutionary operation: A method for increasing industrial productivity. In Journal of the Royal Statistical Society, C, 6(2), pp. 81-101, 1957.

[Bra72]
Branin, F. K.: A widely convergent method for finding multiple solutions of simultaneous nonlinear equations. IBM J. Res. Develop., pp. 504-522, Sept., 1972.

[Bre62]
Bremermann, H. J.: Optimization through evolution and recombination. In Yovits, M. C. et al.: Self-organizing systems. Washington, DC: Spartan Books, pp. 93-106, 1962.

[CEC99]
Angeline, P. J. (ed.): Proceedings of the Congress on Evolutionary Computation. Piscataway, New Jersey, USA: IEEE Press, 1999.

[Cha95]
Chambers, L. (ed.): Genetic Algorithm Applications Vol. I. New York: CRC Press, 1995.

[CS88]
Caruana, R. A. and Schaffer, J. D.: Representation and Hidden Bias: Gray v. Binary Coding for Genetic Algorithms. In Fifth International Conference on Machine Learning, San Mateo, California, USA: Morgan Kaufmann Publishers, pp. 153-161, 1988.

[CES89]
Caruana, R. A., Eshelmann, L. A. and Schaffer, J. D.: Representation and hidden bias II: Eliminating defining length bias in genetic search via shuffle crossover. In Sridharan, N. S. (ed.): Eleventh International Joint Conference on Artificial Intelligence, San Mateo, California, USA: Morgan Kaufmann Publishers, Vol. 1, pp. 750-755, 1989.

[Cav70]
Cavicchio, D. J.: Adaptive search using simulated evolution. Unpublished doctoral dissertation, University of Michigan, Ann Arbor, 1970.

[CF94]
Chipperfield, A. J. and Fleming, P. J.: Parallel Genetic Algorithms: A Survey. Technical Report No. 518, Department of Automatic Control and Systems Engineering, University of Sheffield, 1994.

[CFP94b]
Chipperfield, A. J., Fleming, P. J. and Pohlheim, H.: A Genetic Algorithm Toolbox for MATLAB. Proc. Int. Conf. Sys. Engineering, Coventry, UK, 6-8 Sept., pp. 200-207, 1994.

[CFPF94a]
Chipperfield, A., Fleming, P. J., Pohlheim, H. and Fonseca, C. M.: Genetic Algorithm Toolbox for use with Matlab. Technical Report No. 512, Department of Automatic Control and Systems Engineering, University of Sheffield, 1994.

[Coe99]
Coello, C. A.: List of References on Evolutionary Multiobjective Optimization. Laboratorio Nacional de Informática Avanzada, México, 1999.
http://www.lania.mx/~ccoello/EMOO/EMOObib.html

[CMR91]
Cohoon, J. P., Martin, W. N. and Richards, D.S.: Genetic Algorithms and Punctuated Equilibria in VLSI. In [PPSN1], pp. 134-144, 1991.

[Dav91a]
Davidor, Y.: A Naturally Occurring Niche & Species Phenomenon: The Model and First Results. In [ICGA4], pp. 257-263, 1991.

[Dav91b]
Davidor, Y.: Epistasis Variance: A Viewpoint on GA-Hardness. In [FGA1], pp. 23-35, 1991.

[Dav87]
Davis, L. D.: Genetic Algorithms and Simulated Annealing. San Mateo, California, USA: Morgan Kaufmann Publishers, 1987.

[Dav91]
Davis, L. D.: Handbook of Genetic Algorithms. Van Nostrand Reinhold, 1991.

[DJS93]
De Jong, K. and Spears, W.: On the state of evolutionary computation. In [ICGA5], pp. 618-623, 1993.

[DeJ75]
De Jong, K.: An analysis of the behavior of a class of genetic adaptive systems. Doctoral dissertation, University of Michigan, Dissertation Abstracts International, 36(10), 5140B, University Microfilms No. 76-9381, 1975.

[DS78]
Dixon, L. C. W. and Szego, G. P.: The optimization problem: An introduction. In Dixon, L. C. W. and Szego, G. P. (ed.): Towards Global Optimization II, New York: North Holland, 1978.

[Eas90]
Easom, E. E.: A survey of global optimization techniques. M. Eng. thesis, Univ. Louisville, Louisville, KY, 1990.

[ECJ]
Whitley, D. (ed.): Evolutionary Computation. Journal, Cambridge, Massachusetts: MIT Press, 1993-1999.

[ECT]
Fogel, D. B. (ed.): IEEE Transactions on Evolutionary Computation. Journal, Piscataway, New Jersey, USA: IEEE Press.

[EP96]
Fogel, D. B. (ed.): Evolutionary Programming V, Proceedings of the Fifth Annual Conference on Evolutionary Programming. Cambridge, MA: MIT Press, 1996.

[EP97]
Angeline, P. J., Reynolds, R. G., McDonnell, J. R. and Eberhart, R. (eds.): Evolutionary Programming VI, Proceedings of the Sixth Annual Conference on Evolutionary Programming. Vol. 1213 of Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer-Verlag, 1997.

[EP98]
Porto, V. W., Saravanan, N., Waagen, D. and Eiben, A. E. (eds): Evolutionary Programming VII, Proceedings of the Seventh Annual Conference on Evolutionary Programming. Vol. 1447 of Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer-Verlag, 1998.

[Esh91]
Eshelmann, L. J.: The CHC Adaptive Algorithm: How to have safe search when engaging in Nontraditional Genetic Recombination. In [FGA1], pp. 265-283, 1991.

[Fdb92]
Fogel, D. B.: Evolving Artificial Intelligence. Dissertation, University of California, San Diego, 1992.

[Fdb94a]
Fogel, D. B.: An Introduction to Simulated Evolutionary Optimization. IEEE Trans. on Neural Networks: Special Issue on Evolutionary Computation, Vol. 5, No. 1, pp. 3-14, 1994.

[Fdb94b]
Fogel, D. B.: Applying Evolutionary Programming to Selected Control Problems. Comp. Math. App., 11(27), pp. 89-104, 1994.

[FOW66]
Fogel, L. J., Owens, A. J. and Walsh, M. J.: Artificial Intelligence through Simulated Evolution. New York: John Wiley, 1966.

[FF93]
Fonseca, C. M. and Fleming, P. J.: Genetic Algorithms for Multiple Objective Optimization: Formulation, Discussion and Generalization. In [ICGA5], pp. 416-423, 1993.

[FF95a]
Fonseca, C. M. and Fleming, P. J.: Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms I: A Unified Formulation. Research report 564, Dept. Automatic Control and Systems Eng., University of Sheffield, Sheffield, U.K., 1995.

[FF95b]
Fonseca, C. M. and Fleming, P. J.: Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms II: Application Example. Research report 565, Dept. Automatic Control and Systems Eng., University of Sheffield, Sheffield, U.K., 1995.

[FF95c]
Fonseca, C. M. and Fleming, P. J.: An Overview of Evolutionary Algorithms in Multiobjective Optimization. Evolutionary Computation, 3(1), pp. 1-16, 1995.

[Fon95]
Fonseca, C. M.: Multiobjective Genetic Algorithms with Application to Control Engineering Problems. Ph.D. Thesis, Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, U.K., 1995.

[FF96]
Fonseca, C. M. and Fleming, P. J.: On the Performance Assessment and Comparison of Stochastic Multiobjective Optimizers. In [PPSN4], pp.584-593, 1996.

[For81]
Forsyth, R.: BEAGLE - A Darwinian Approach to Pattern Recognition. Kybernetes, 10, pp. 159-166, 1981.

[Fra62]
Fraser, A. S.: Simulation of genetic systems. Journal of Theoretical Biology, 2, pp. 329-346, 1962.

[Fri58]
Friedberg, R. M.: A learning machine: Part I. IBM Journal, 2(1), pp. 2-13, 1958.

[FDN59]
Friedberg, R. M., Dunham, B. and North, J. H.: A learning machine: Part II. IBM Journal, 3(7), pp. 282-287, 1959.

[FGA1]
Rawlins, G. J. E.: Foundations of Genetic Algorithms. San Mateo, California, USA: Morgan Kaufmann Publishers, 1991.

[FGA2]
Whitley, L. D.: Foundations of Genetic Algorithms 2. San Mateo, California, USA: Morgan Kaufmann Publishers, 1993.

[FGA3]
Whitley, L. D. and Vose, M. D.: Foundations of Genetic Algorithms 3. San Francisco, California, USA: Morgan Kaufmann Publishers, 1995.

[FGA4]
Belew, R. K. and Vose, M. D.: Foundations of Genetic Algorithms 4. San Francisco, California, USA: Morgan Kaufmann Publishers, 1997.

[FGA5]
Banzhaf, W. and Reeves, C.: Foundations of Genetic Algorithms 5. San Francisco, California, USA: Morgan Kaufmann Publishers, 1999.

[GAOT]
Houck, C., Joines, J. and Kay, M.: The Genetic Algorithm Optimization Toolbox (GAOT). North Carolina State University, Department of Industrial Engineering, NCSU-IE TR 95-09, 1995.
http://www.ie.ncsu.edu/gaot/

[GEC99]
Banzhaf, W. (ed.): GECCO'99 - Proceedings of the Genetic and Evolutionary Computation Conference, San Francisco, CA: Morgan Kaufmann, 1999.

[GP96]
Koza, J. R., Goldberg, D. E., Fogel, D. B. and Riolo, R. L.: Genetic Programming 1996: Proceedings of the First Annual Conference. Cambridge: MIT Press, 1996.

[GP97]
Koza, J. R. et al. (eds.): Genetic Programming 1997: Proceedings of the Second Annual Conference. San Francisco, CA: Morgan Kaufmann, 1997.

[GP98]
Koza, J. R. et al. (eds.): Genetic Programming 1998: Proceedings of the Third Annual Conference. San Francisco, CA: Morgan Kaufmann, 1998.

[Gol83]
Goldberg, D. E.: Computer-aided gas pipeline operation using genetic algorithms and rule learning. Doctoral dissertation, University of Michigan, Dissertation Abstracts International, 44(10), 3174B, University Microfilms No. 8402282, 1983.

[Gol87]
Goldberg, D. E.: Simple Genetic Algorithms and the Minimal Deceptive Problem. In [Dav87], pp. 74-88, 1987.

[Gol89]
Goldberg, D. E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, Mass.: Addison-Wesley, 1989.

[GD91]
Goldberg, D. E. and Deb, K.: A Comparative Analysis of Selection Schemes Used in Genetic Algorithms. In [FGA1], pp. 69-93, 1991.

[GP71]
Goldstein, A. A. and Price, I. F.: On descent from local minima. Math. Comput., Vol. 25, No. 115, 1971.

[Gre86]
Grefenstette, J. J.: Optimization of Control Parameters for Genetic Algorithms. In IEEE Transactions on Systems, Man and Cybernetics, 16 (1986) 1, pp.122-128, 1986.

[GB89]
Grefenstette, J. J. and Baker, J. E.: How Genetic Algorithms Work: A Critical Look at Implicit Parallelism. In [ICGA3], pp. 20-27, 1989.

[Gre93]
Grefenstette, J. J.: Deception Considered Harmful. In [FGA2], pp. 75-91, 1983.

[HH94]
Haas, R. and Hunt, K. J.: Genetic based optimisation of a fuzzy-neural vehicle controller. Technical Report, Daimler Benz AG, Research and Technology Berlin, 1994.

[Ham97]
Hammel, U.: Evolutionary Computation Applications: Simulation models. In [HEC97], F1.8, pp. F1.8:1-F1.8:9, 1997.

[Han98]
Hansen, N.: Verallgemeinerte individuelle Schrittweitenregelung in der Evolutionsstrategie - eine Untersuchung zur entstochastisierten, koordinatensystemunabhängigen Adaption der Mutationsverteilung. Berlin: Mensch & Buch Verlag, 1998

[HGO95]
Hansen, N., Gawelczyk, A. and Ostermeier, A.: Sizing the Population with Respect to the Local Progress in (1,_)-Evolution Strategies - A Theoretical Analysis. In [ICEC95], pp. 80-85, 1995.

[HH98]
Haupt, R. L. and Haupt, S. E.: Practical Genetic Algorithms. NewYork: John Wiley & Sons, 1998.

[HB91]
Hoffmeister, F. and Bäck, T.: Genetic Algorithms and Evolutionary Strategies: Similarities and Differences. In [PPSN1], pp. 455-469, 1991.

[HEC97]
Bäck, T., Fogel, D. B. and Michalewicz, Z. (eds.): Handbook on Evolutionary Computation. Bristol: Institute of Physics Publishing and Oxford, New York: Oxford University Press, 1997.

[Hol75]
Holland, J. H.: Adaptation in natural and artificial systems. Ann Arbor: The University of Michigan Press, 1975.

[Hol95]
Holland, J. H.: Hidden order: how adaptation builds complexity. Reading, Massachusetts: Addison-Wesley, 1995.

[Hoo95]
Hooker, J. N.: Testing Heuristics: We Have It All Wrong. Journal of Heuristics, 1 (1995), pp. 33-42, 1995.

[HN93]
Horn, J. and Nafpliotis, N.: Multiobjective optimization using the niched pareto genetic algorithm. IlliGAL Report 93005, Illinois Genetic Algorithms Laboratory, University of Illinois, Urbana, Champaign, 1993.

[HG95]
Horn, J. and Goldberg, D. E.: Genetic Algorithm Difficulty and the Modality of Fitness Landscapes. In [FGA3], pp. 243-269, 1995.

[Hor97]
Horn, J.: Evolutionary Computation Applications: Multicriterion decision making. In [HEC97], F1.9, pp. F1.9:1-F1.9:15, 1997.

[ICEC94]
Fogel, D. B.: Proceedings of The First IEEE Conference on Evolutionary Computation, Piscataway, New Jersey, USA: IEEE Service Center, 1994.

[ICEC95]
Proceedings of the Second IEEE Conference on Evolutionary Computation 1995, Piscataway, New Jersey, USA: IEEE Press, 1995.

[ICEC96]
Proceedings of the 1996 IEEE Conference on Evolutionary Computation, Piscataway, New Jersey, USA: IEEE Press, 1996.

[ICEC97]
Proceedings of the 1997 IEEE Int. Conf. on Evolutionary Computation, Piscataway, New Jersey, USA: IEEE Press, 1997.

[ICEC98]
Proceedings of the 1998 IEEE Int. Conf. on Evolutionary Computation, Piscataway, New Jersey, USA: IEEE Press, 1998.

[ICGA1]
Grefenstette, J. J. (ed.): Proceedings of an International Conference on Genetic Algorithms and their Application, Hillsdale, New Jersey, USA: Lawrence Erlbaum Associates, 1985.

[ICGA2]
Grefenstette, J. J. (ed.): Proceedings of the Second International Conference on Genetic Algorithms and their Application, Hillsdale, New Jersey, USA: Lawrence Erlbaum Associates, 1987.

[ICGA3]
Schaffer, J. D. (ed.): Proceedings of the Third International Conference on Genetic Algorithms, San Mateo, California, USA: Morgan Kaufmann Publishers, 1989.

[ICGA4]
Belew, R. K. and Booker, L. B. (eds.): Proceedings of the Fourth International Conference on Genetic Algorithms, San Mateo, California, USA: Morgan Kaufmann Publishers, 1991.

[ICGA5]
Forrest, S. (ed.): Proceedings of the Fifth International Conference on Genetic Algorithms, San Mateo, California, USA: Morgan Kaufmann Publishers, 1993.

[ICGA6]
Eshelman, L. J. (ed.): Proceedings of the Sixth International Conference on Genetic Algorithms, San Francisco, California, USA: Morgan Kaufmann Publishers, 1995.

[ICGA7]
Bäck, T. (ed.): Proceedings of the Seventh International Conference on Genetic Algorithms, San Francisco, California, USA: Morgan Kaufmann Publishers, 1997.

[Jac95]
Jacob, C.: MathEvolvica - Simulierte Evolution von Entwicklungsprogrammen der Natur. Dissertation, Arbeitsberichte des Instituts für mathematische Maschinen und Datenverarbeitung (Informatik), Universität Erlangen-Nürnberg, Band 28, Nummer 10, 1995.

[Koz92]
Koza, J. R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge: MIT Press, 1992.

[Koz94]
Koza, J. R.: Genetic Programming II: Automatic Discovery of Reusable Programs. Cambridge: MIT Press, 1994.

[Koz99]
Koza, J. R., Bennett, F. H., Andre, D. and Keane, M. A.: Genetic Programming III: Darwinian Invention and Problem Solving. San Francisco, CA: Morgan Kaufmann, 1999.

[KS79]
Kreisselmeier, G. and Steinhauser, R.: Systematische Auslegung von Reglern durch Optimierung eines vektoriellen Gütekriteriums. In Regelungstechnik, 3, pp. 76-79, 1979.

[Lan95]
Langermann: Definition of a test function for contest on Evolutionary Computation. In [ICEC95], 1995.

[Lit92]
Littger, K.: Optimierung - Eine Einführung in rechnergestützte Methoden und Anwendungen. Berlin, Heidelberg: Springer-Verlag, 1992.

[MBC95]
Marenbach, P., Bettenhausen, K.D. and Cuno, B.: Selbstorganisierende Generierung strukturierter Prozeßmodelle. at-Automatisierungstechnik 6 (1995), pp. 277-288, Berlin, 1995.

[MBF96]
Marenbach, P., Bettenhausen, K. D. and Freyer, S.: Signal path oriented approach to generation of dynamic process models, in [GP96], pp. 327-332, 1996.

[MW94]
MathWorks, The: Matlab - User Guide. Natick, Mass.: The MathWorks, Inc., 1994.
http://www.mathworks.com/

[MHF92]
Mecklenburg, K., Hrycej, T., Franke, U. and Fritz, H.: Neural control of autonomous vehicle. In IEEE Vehicular Technology Conference, Denver, 1992.

[Men2]
Osmera, P.: MENDEL'96 - 2nd International Conference on Genetic Algorithms. 26.-28. June 1996, Technical University of Brno, Czech Republic, 1996.

[Mic92]
Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Berlin, Heidelberg, New York: Springer-Verlag, 1992.

[Mic94]
Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs, Second, Extended Edition. Berlin, Heidelberg, New York: Springer-Verlag, 1994.

[Mie99]
Miettinen, K. M.: Nonlinear multiobjective optimization. Boston, London, Dordrecht: Kluwer Academic Publishers, 1999.

[Mit96]
Mitchell, M.: An Introduction to Genetic Algorithms. Cambridge, Massachusetts: MIT Press, 1996.

[Mit90]
Mitschke, M.: Dynamik der Kraftfahrzeuge: Band C, Fahrverhalten. Berlin, Heidelberg, New York: Springer-Verlag, 1990.

[Müh94]
Mühlenbein, H.: The Breeder Genetic Algorithm - a provable optimal search algorithm and its application. Colloquium on Applications of Genetic Algorithms, IEE 94/067, London, 1994.

[Müh95b]
Mühlenbein, H.: Genetische Algorithmen und Evolutionsstrategien - Auf der Suche nach verschollenen Schätzen. GMD-Spiegel 2/95, 1995.
http://borneo.gmd.de/AS/gmdsp/muehlen.html

[MSV93a]
Mühlenbein, H. and Schlierkamp-Voosen, D.: Predictive Models for the Breeder Genetic Algorithm: I. Continuous Parameter Optimization. Evolutionary Computation, 1 (1), pp. 25-49, 1993.
ftp://borneo.gmd.de/pub/as/ga/gmd_as_ga-93_01.ps

[MSV95]
Mühlenbein, H. and Schlierkamp-Voosen, D.: Analysis of Selection, Mutation and Recombination in Genetic Algorithms. In Banzhaf, W. and Eeckman, F. H.: Evolution as a Computational Process. Lecture Notes in Computer Science 899, pp. 142-168, Berlin: Springer-Verlag, 1995.
ftp://borneo.gmd.de/pub/as/ga/gmd_as_ga-95_03.ps

[Nis97]
Nissen, V.: Einführung in evolutionäre Algorithmen: Optimierung nach dem Vorbild der Evolution. Braunschweig, Wiesbaden: Vieweg, 1997.

[Ost97]
Ostermeier, A.: Schrittweitenadaption in der Evolutionsstrategie mit einem entstochastisierten Ansatz. Dissertation, Technische Universität Berlin, Fachbereich 6, 1997.

[OGH94]
Ostermeier, A., Gawelczyk, A. and Hansen, N.: Step-size adaptation based on non-local use of selection information. In [PPSN3], pp. 189-198, 1994.

[Pad97]
Institut für angewandte Daten- und Wissenstechnik: Prognose der minimalen Ausführungszeiten von Echtzeit-Systemen auf Basis von genetisch erzeugten Testfallmengen - Version 1.0. Institut für angewandte Daten- und Wissenstechnik AD/WT, Universität Paderborn, 1997.

[Poh93]
Pohlheim, H.: Simulation und Optimierung eines Blaualgen-Wachstums-Modells. Diplomarbeit, Technische Universität Ilmenau, 1993.

[Poh95]
Pohlheim, H.: Ein genetischer Algorithmus mit Mehrfachpopulationen zur Numerischen Optimierung. at-Automatisierungstechnik 3 (1995), pp. 127-135, 1995.

[GEATbx]
Pohlheim, H.: GEATbx: Genetic and Evolutionary Algorithm Toolbox for use with Matlab. www.geatbx.com, 1995-1999.
http://www.geatbx.com/index.html

[Poh97]
Pohlheim, H.: Advanced Techniques for the Visualization of Evolutionary Algorithms. Proceedings of 42. International Scientific Colloquium Ilmenau, Vol. 3, pp. 60-68, 1997.
http://www.pohlheim.com/papers_pohlheim.html

[Poh98]
Pohlheim, H.: Entwicklung und systemtechnische Anwendung Evolutionärer Algorithmen. Aachen, Germany: Shaker Verlag, 1998. (Development and Engineering Application of Evolutionary Algorithms)
http://www.pohlheim.com/diss/index.html

[Poh99]
Pohlheim, H.: Visualization of Evolutionary Algorithms - set of standard techniques and multidimensional visualization. In [GEC99], p. 533-540, 1999.
http://www.pohlheim.com/papers_pohlheim.html

[PH96a]
Pohlheim, H. und Heißner, A.: Optimale Steuerung der Zustandsgrößen im Gewächshaus mit Genetischen Algorithmen: Grundlagen, Verfahren und Ergebnisse. Technischer Bericht, Technische Universität Ilmenau, 1996.

[PH96b]
Pohlheim, H. and Heißner, A.: Anwendung genetischer Algorithmen zur optimalen Steuerung des Gewächshausklimas. In GMA-Kongreß'96, VDI-Berichte 1282, pp. 799-809, Düsseldorf: VDI-Verlag, 1996.

[PH97a]
Pohlheim, H. and Heißner, A.: Optimal Control of Greenhouse Climate using a Short Time Greenhouse Climate Model and Evolutionary Algorithms. In Proceedings of 3^rd IFAC/ISHS Workshop on ,,Mathematical and Control Applications in Agriculture & Horticulture", pp. 113-118, 1997.

[PM96]
Pohlheim, H. and Marenbach, P.: Generation of structured process models using genetic programming. In [AISB96], pp. 102-109, 1996.
http://www.pohlheim.com/papers_pohlheim.html

[PPW99]
Pohlheim, H., Pawletta, S. and Westphal, A.: Parallel Evolutionary Optimization under Matlab on standard computing networks. In [GEC99], Evolutionary Computation and Parallel Processing Workshop, pp. 174-176, 1999.
http://www.pohlheim.com/papers_pohlheim.html

[PS98]
Pohlheim, H. und Schütte, A.: Optimierung der Parameter in einem Verbrennungsmodell für einen Dieselmotor mit Evolutionären Algorithmen. interner Technischer Bericht FT3/A-1998-001, Daimler Benz AG, 1998.

[PW99]
Pohlheim, H. and Wegener, J.: Testing the Temporal Behavior of Real-Time Software Modules using Extended Evolutionary Algorithms. In [GEC99], p. 1795, 1999.
http://www.pohlheim.com/papers_pohlheim.html

[PPA93]
Puta, H., Pohlheim, H. and Affa, I.: Simulation und Entscheidungshilfe für das Ökosystem Barther Bodden. In VDI-Berichte 1067, pp. 429-440, Düsseldorf: VDI-Verlag, 1993.

[PPSN1]
Schwefel, H.-P. and Männer, R.: Parallel Problem Solving from Nature - PPSN I. Vol. 496 of Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer-Verlag, 1991.

[PPSN2]
Männer, R. and Manderick, B.: Parallel Problem Solving from Nature, 2. Amsterdam: Elsevier Science Publishers, 1992.

[PPSN3]
Davidor, Y., Schwefel, H.-P. and Männer, R.: Parallel Problem Solving from Nature - PPSN III: International Conference on Evolutionary Computation. Vol. 866 of Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer-Verlag, 1994.

[PPSN4]
Voigt, H.-M., Ebeling, W., Rechenberg, I. and Schwefel, H.-P.: Parallel Problem Solving from Nature - PPSN IV: International Conference on Evolutionary Computation. Vol. 1141 of Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer-Verlag, 1996.

[PPSN5]
Voigt, H.-M., Ebeling, W., Rechenberg, I. and Schwefel, H.-P.: Parallel Problem Solving from Nature - PPSN V: International Conference on Evolutionary Computation. Vol. 1498 of Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer-Verlag, 1998.

[Ray94]
Ray, T. S.: An evolutionary approach to synthetic biology: Zen and the art of creating life. Artificial Life, 1 (1/2), pp. 195-226, 1994.

[Rec73]
Rechenberg, I.: Evolutionsstrategie - Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. Stuttgart: Frommann-Holzboog, 1973.

[Rec94]
Rechenberg, I.: Evolutionsstrategie 94. Stuttgart: Frommann-Holzboog, 1994.

[RB94]
Renders, J.-M. and Bersini, H.: Hybridizing Genetic Algorithms with hill-climbing Methods for Global Optimization: Two Possible Ways. In [ICEC94], Vol. I, pp. 312-317, 1994.

[RB93]
Riedmiller, M. and Braun, H.: A direct adaptive method for faster backpropagation learning: The RPROP algorithm. In H. Ruspini (ed.): Proceedings of the IEEE International Conference on Neural Networks (ICNN), pp.586-591, 1993.

[Sch68]
Schwefel, H.-P.: Projekt MHD-Staustrahlrohr: Experimentelle Optimierung einer Zweiphasendüse, Teil I. Technischer Bericht 11.034/68, 35, AEG Forschungsinstitut, Berlin, 1968.

[Sch75]
Schwefel, H.-P.: Evolutionsstrategie und numerische Optimierung. Dissertation, Technische Universität Berlin, 1975.

[Sch81]
Schwefel, H.-P.: Numerical optimization of computer models. Chichester: Wiley & Sons, 1981.

[Sch95]
Schwefel, H.-P.: Evolution and optimum seeking. New York: John Wiley & Sons, 1995.

[SK92]
Schwefel, H. P. and Kursawe, F.: Künstliche Evolution als Modell für natürliche Intelligenz. In Nachtigall, W. (Ed.): Technische Biologie und Bionik 1, Proceedings 1. Bionik-Kongreß, BIONA report 8, Stuttgart: G. Fischer, pp. 73-91, 1992.

[SHF94]
Schöneburg, E., Heinzmann, F. and Feddersen, S.: Genetische Algorithmen und Evolutionsstrategien. Bonn, Paris, Reading, Mass.: Addison-Wesley, 1994.

[SDJ91a]
Spears, W.M. and De Jong, K. A.: On the Virtues of Parameterised Uniform Crossover. In [ICGA4], pp. 230-236, 1991.

[SDJ91b]
Spears, W.M. and De Jong, K. A.: An Analysis of Multi-Point Crossover. In [FGA1], pp. 301-315, 1991.

[SD94]
Srinivas, N. and Deb, K.: Multiobjective Optimization using nondominated sorting in genetic algorithms. Evolutionary Computation, 2(3), pp. 221-248, 1994.

[SE92]
Stuckmann, B. E. and Easom, E. E.: A Comparison of Bayesian Sampling and Global Optimization Techniques. IEEE Transactions on Systems, Man, and Cybernetics, Vol. 22, No. 5, pp.1024-1032, 1992.

[Sum95]
Sumser, S.: Verbrennungsmodell für direkteinspritzende Dieselmotoren. interner Technischer Bericht F1M/ST 95-0036, Daimler Benz AG, 1995.

[SR96]
Surry, P. D. and Radcliffe, N. J.: Innoculation to Initialise Evolutionary Search. In [AISB96], pp. 260-275, 1996.

[Sys89]
Syswerda, G.: Uniform crossover in genetic algorithms. In [ICGA3], pp. 2-9, 1989.

[TZ89]
Törn, A. and Zilinskas, A.: Global Optimization. Vol. 350 of Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer-Verlag, 1989.

[Vel99]
Veldhuizen, D. A. van.: Multiobjective Evolutionary Algorithms: Classifications, Analyses, and New Innovations. PhD thesis, Department of Electrical and Computer Engineering. Graduate School of Engineering. Air Force Institute of Technology, Wright-Patterson AFB, Ohio, 1999.
http://www.lania.mx/~ccoello/EMOO/veldhuizen99a.ps.gz

[Vös97]
Vössner, S.: Convergence Measures for Genetic Algorithms. Technical Report, Stanford University, Department of EES, Operations Research, 1997.

[VA94]
Voigt, H.-M. and Anheyer, T.: Modal Mutations in Evolutionary Algorithms. In [ICEC94], Vol. I, pp. 88-92, 1994.

[Wei70]
Weinberg, R.: Computer simulation of a living cell. Doctoral dissertation, University of Michigan, Dissertation Abstracts International, 31(9), 5312B, University Microfilms No. 71-4766, 1970.

[Why89]
Whitley, D.: The GENITOR Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best. In [ICGA3], pp. 116-121, 1989.

[Wri91]
Wright, A. H.: Genetic Algorithms for Real Parameter Optimization. In [FGA1], pp. 205-218, 1991.

[ZT98]
Zitzler, E. and Thiele, L.: An Evolutionary Algorithm for Multiobjective Optimization: The Strength Pareto Approach. Technical Report 43, Computer Engineering and Communication Networks Lab (TIK), Swiss Federal Institute of Technology (ETH) Zurich, 1998.
ftp://ftp.tik.ee.ethz.ch/pub/people/zitzler/ZT1998a.ps

[ZDT99]
Zitzler, E., Deb, K. and Thiele, L.: Comparison of Multiobjective Evolutionary Algorithms: Empirical Results. Technical Report 70, Computer Engineering and Communication Networks Lab (TIK), Swiss Federal Institute of Technology (ETH) Zurich, 1999.
ftp://ftp.tik.ee.ethz.ch/pub/people/zitzler/ZDT1999a.ps

"Evolutionäre Algorithmen - Verfahren, Operatoren, Hinweise aus der Praxis"

Literaturverzeichnis (Evolutionäre Algorithmen)

Evolutionäre Algorithmen und Optimierung

Literaturverzeichnis
(Evolutionäre Algorithmen)