Entw. und Anw. von EA: 9.1 Literaturverzeichnis 48

9.1.2 Behandlung von Populationen - Parallele Modelle

9.1.4 Polyploidie bei Evolutionären Algorithmen

9.1.5 Biologie, Genetik und Populationsgenetik

9.1 Literaturverzeichnis

Das Literaturverzeichnis enthält die Literatur, die bei der Entstehung dieser Arbeit verwendet wurde. Um eine bessere Übersichtlichkeit zu gewährleisten, wurden die Einträge entsprechend den in dieser Arbeit vertiefend behandelten Gebieten geordnet. Dadurch wird es möglich, sich einen schnellen Überblick der auf dem jeweiligen Gebiet wichtigen und interessanten Arbeiten zu verschaffen.

9.1.1 Evolutionäre Algorithmen

[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, volume 1143 of Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer-Verlag, 1996.

[Alt95] Altenberg, L.: The Schema Theorem and Price's Theorem. in [FGA3], pp. 23-49, 1995. http://pueo.mhpcc.edu/~altenber/PAPERS/STPT/

[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.

[Bäc93] Bäck, T.: Optimal Mutation Rates in Genetic Search. in [ICGA5], pp. 2-8, 1993.
http://lumpi.informatik.uni-dortmund.de/people/baeck/papers/icga93.ps.Z

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

[BS93] Bäck, T. and Schwefel, H.-P.: An overview of evolutionary algorithms for parameter optimization. Evolutionary Computation, 1(1), pp. 1-23, 1993.
http://lumpi.informatik.uni-dortmund.de/people/baeck/papers/ec93.ps.Z

[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

[BM96] 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

[Bli97] Blickle, T.: Theory of Evolutionary Algorithms and Application to System Synthesis. Ph.D. thesis. TIK-Schriftenreihe Nr. 17., Zürich: vdf Verlag, 1997.
http://www.tik.ee.ethz.ch/~blickle/diss.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.

[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, pp. 153-161, San Mateo, California, USA: Morgan Kaufmann Publishers, 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 Eleventh International Joint Conference on Artificial Intelligence, Sridharan, N. S. (Ed.), vol. 1, pp. 750-755, San Mateo, California, USA: Morgan Kaufmann Publishers, 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.

[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. (Eds.), 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] DeJong, K. (Ed.): Evolutionary Computation. Journal, Cambridge, Massachusetts: MIT Press.

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

[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.

[Fdb95] Fogel, D. B.: Evolutionary computation: toward a new philosophy of machine intelligence. New York: IEEE Press, 1995.
http://www.natural-selection.com/misc/evolCompBook.html

[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.

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

[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.

[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.

[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.

[HOG95] Hansen, N., Ostermeier, A. and Gawelczyk, A.: On the Adaptation of Arbitrary Mutation Distributions in Evolution Strategies: The Generating Set Adaptation. in [ICGA6], pp. 57-64, 1995.
ftp://ftp-bionik.fb10.tu-berlin.de/pub/papers/Bionik/GSAES.ps.Z

[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.

[HO96] Hansen, N. and Ostermeier, A.: Adapting Arbitrary Normal Mutation Distributions in Evolution Strategies: The Covariance Matrix Adaptation. in [ICEC96], pp. 312-317, 1996.
ftp://ftp-bionik.fb10.tu-berlin.de/pub/papers/Bionik/CMAES.ps.Z

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

[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.

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

[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 Third IEEE Conference on Evolutionary Computation 1996, Piscataway, New Jersey, USA: IEEE Press, 1996.

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

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

[ICGA3] Schaffer, J. D.: 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.: Proceedings of the Fourth International Conference on Genetic Algorithms, San Mateo, California, USA: Morgan Kaufmann Publishers, 1991.

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

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

[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.

[JF95] Jones, T. and Forrest, S.: Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms. in [ICGA6], pp. 184-192, 1995.
http://www.santafe.edu/sfi/publications/Working-Papers/95-02-022.ps

[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.

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

[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/

[Mat96] Mattfeld, D. C.: Evolutionary Search and the Job Shop: Investigations on Genetic Algorithms for Production Scheduling. Heidelberg: Physica-Verlag, 1996.

[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.

[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.

[Müh95a] Mühlenbein, H.: Adaptive Systeme in offenen Welten. GMD-Spiegel 2/95, 1995.
http://borneo.gmd.de/AS/gmdsp/editorial.html

[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, pages 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.

[OGH93] Ostermeier, A., Gawelczyk, A. and Hansen, N.: A Derandomized Approach to Self Adaptation of Evolution Strategies. Technical Report TR-93-003, TU Berlin, 1993.
ftp://ftp-bionik.fb10.tu-berlin.de/pub/papers/Bionik/tr-03-93.ps.Z

[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.

[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.

[Poh96] Pohlheim, H.: Genetic and Evolutionary Algorithm Toolbox for use with Matlab - Documentation. Technical Report, Technical University Ilmenau, 1995-1997.

[Poh97] Pohlheim, H.: Advanced Techniques for the Visualization of Evolutionary Algorithms. Proceedings of 42. International Scientific Colloquium Ilmenau, vol. 3, pp. 60-68, 1997.

[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.: Optimal Control of Greenhouse Climate using Genetic Algorithms. in [Men2], pp. 112-119, 1996.

[PH96c] 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 Evolutionary Algorithms. Proceedings of 42. International Scientific Colloquium Ilmenau, vol. 3, pp. 9-16, 1997.

[PH97b] Pohlheim, H. and Heißner, A.: Optimal Control of Greenhouse Climate using a Short Time Greenhouse Climate Model and Evolutionary Algorithms. 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.

[PL96] Poli, R. and Logan, B.: Evolutionary Computation Cookbook: Recipes for Designing New Algorithms, Second Online Workshop on Evolutionary Computation, Japan, 1996.
http://www.bioele.nuee.nagoya-u.ac.jp/wec2/papers/index.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. volume 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. volume 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. volume 1141 of Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer-Verlag, 1996.

[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.

[Ric95] Richter, G.: Adaptive Systeme: Computer passen sich an. GMD-Spiegel 2/95, 1995.
http://borneo.gmd.de/AS/gmdsp/richter.html

[RB93] Riedmiller, M. and Braun, H.: A direct adaptive method for faster backpropagation learning: The RPROP algorithm. in H. Ruspini (editor), 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.

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

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

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

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

[VMC95] Voigt, H.-M., Mühlenbein, H. and Cvetkovi, D.: Fuzzy recombination for the continuous Breeder Genetic Algorithm. in [ICGA6], pp. 104-111, 1995.
ftp://borneo.gmd.de/pub/as/ga/gmd_as_ga-95_01.ps

[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.

[WM95] Wolpert, D. H. and Macready, W. G.: No free lunch theorems for search. Technical report SFI-TR-95-02-010, The Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM, 87501, USA, 1995.
http://www.santafe.edu/sfi/publications/Working-Papers/95-02-010.ps

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

9.1.2 Behandlung von Populationen - Parallele Modelle

[Bel95] Belding, T. C.: The Distributed Genetic Algorithm Revisited. in [ICGA6], pp.114-121, 1995.

[Can95] Cantú-Paz, E.: A Summary of Research on Parallel Genetic Algorithms. Technical Report IlliGAL No. 95007, July 1995, University of Illinois at Urbana-Champaign, 1995.
ftp://ftp-illigal.ge.uiuc.edu/pub/papers/IlliGALs/95007.ps.Z

[CJ91] Collins, R. J. and Jefferson, D. R.: Selection in Massively Parallel Genetic Algorithms. in [ICGA4], pp. 249-256, 1991.

[CPR96] Corno, F., Prinetto, P., Rebaudengo, M. and Reorda, M. S.: Exploiting Competing Subpopulations for Automatic Generation of Test Sequences for Digital Circuits. in [PPSN4], pp. 792-800, 1996.

[DJS95] DeJong, K. and Sarma, J.: On Decentralizing Selection Algorithms. in [ICGA6], pp. 17-23, 1995.

[FH91] Fogarty, T. C. and Huang, R.: Implementing the Genetic Algorithm on Transputer Based Parallel Processing Systems. in [PPSN1], pp. 145-149, 1991.

[GW91] Gordon, V. S. and Whitley, D.: Serial and Parallel Genetic Algorithms as Function Optimizers. in [ICGA5], pp. 177-183, 1993.

[GS89] Gorges-Schleuter, M.: ASPARAGOUS An Asynchronous Parallel Genetic Optimization Strategy. in [ICGA3], pp. 422-427, 1989.

[GS91] Gorges-Schleuter, M.: Explicit Parallelism of Genetic Algorithms through Population Structures. in [PPSN1], pp. 150-159, 1991.

[HM94] Hauser, R. and Männer, R.: Implementation of Standard Genetic Algorithms on MIMD Machines. in [PPSN3], pp. 504-513, 1994.

[Her92] Herdy, M.: Reproductive Isolation as Strategy Parameter in Hierarchical Organized Evolution Strategies. in [PPSN2], pp. 207-217, 1992.

[KSR94] Kapsalis, A., Smith, G.D. and Rayward-Smith, V.J.: A unified parallel genetic algorithm. AISB Workshop Evolutionary Computation, April 11-13, Leeds, 1994.

[Loh91] Lohmann, R.: Application of Evolution Strategy in Parallel Populations. in [PPSN1], pp. 198-208, 1991.

[MS89] Manderick, B. and Spiessens, P.: Fine-grained Parallel Genetic Algorithms. in [ICGA3], pp. 428-433, 1989.

[Müh89] Mühlenbein, H.: Parallel genetic algorithms, population genetics and combinatorial optimization. in [ICGA3], pp. 416-421, 1989.

[Müh91] Mühlenbein, H.: Evolution in Time and Space - The Parallel Genetic Algorithm. in [FGA1], pp. 316-337, 1991.
ftp://borneo.gmd.de/pub/as/ga/gmd_as_ga-91_01.ps

[MGK88] Mühlenbein, H., Gorges-Schleuter, M. and Krämer, O.: Evolution algorithms in combinatorial optimization. Parallel Computing, 7, pp.65-85, 1988.

[MSB91] Mühlenbein, H., Schomisch, M. and Born, J.: The parallel genetic algorithm as function optimizer. Parallel Computing, 17, pp.619-632, 1991.

[MSV93a] siehe S.

[PLG87] Pettey, C. B., Leuze, M. R. and Grefenstette, J. J.: A Parallel Genetic Algorithm. in [ICGA2], pp. 155-161, 1987.

[Rob87] Robertson, G. G.: Parallel Implementation of Genetic Algorithms in a Classifier System. in [ICGA2], pp. 140-147, 1987.

[Rud91] Rudolph, G.: Global Optimization by Means of Distributed Evolution Strategies. in [PPSN1], pp. 209-213, 1991.

[SDJ96] Sarma, J. and DeJong, K.: An Analysis of the Effects of Neighbourhood Size and Shape on Local Selection Algorithms. in [PPSN4], pp. 236-244, 1996.

[Swm96] Schwehm, M.: Globale Optimierung mit massiv parallelen genetischen Algorithmen. Dissertation, Universität Erlangen-Nürnberg, 1996.
http://www7.informatik.uni-erlangen.de/~schwehm/MYpapers/Dissertation.html

[SM91] Spiessens, P. and Manderick, B.: A Massively Parallel Genetic Algorithms - Implementation and First Analysis. in [ICGA4], pp. 279-286, 1991.

[SVM94] Schlierkamp-Voosen, D. and Mühlenbein, H.: Strategy adaptation by competing subpopulations. in [PPSN3], pp. 199-208, 1994.
ftp://borneo.gmd.de/pub/as/ga/gmd_as_ga-94_14.ps

[SVM96] Schlierkamp-Voosen, D. and Mühlenbein, H.: Adaptation of Population Sizes by Competing Subpopulations. in [ICEC96], pp. 330-335, 1996.
ftp://borneo.gmd.de/pub/as/ga/gmd_as_ga-96_01.ps

[SWM91] Starkweather, T. Whitley, D. and Mathias, K.: Optimization using Distributed Genetic Algorithms. in [PPSN1], pp. 176-185, 1991.

[Tan87] Tanese, R.: Parallel Genetic Algorithm for a Hypercube. in [ICGA2], pp. 177-183, 1987.

[Tan89] Tanese, R.: Distributed Genetic Algorithms. in [ICGA3], pp. 434-439, 1989.

[VBS91] Voigt, H.-M., Born, J. and Santibanez-Koref, I.: Modeling and Simulation of Distributed Evolutionary Search Processes for Function Optimization. in [PPSN1], pp. 373-380, 1991.

[VSB92] Voigt, H.-M., Santibanez-Koref, I. and Born, J.: Hierarchically Structured Distributed Genetic Algorithm. in [PPSN2], pp. 145-154, 1992.

9.1.3 Visualisierung

[CB96] Beardah, C. C. and Baxter, M.: The archaeological use of Kernel Density Estimates. Internet Archaeology 1, 5.1, 1996.
http://intarch.ac.uk/journal/issue1/beardah_toc.html

[Col93] Collins, T. D.: The Visualisation of Genetic Algorithms. Msc. Thesis, De Montfort University, Leicester, GB, 1993.

[Col95] Collins, T. D.: The Visualization of Genetic Algorithms - Related Work. Technical Report, KMI-TR-19, Knowledge Media Institute, The Open University, Milton Keynes, UK, 1995.
http://kmi.open.ac.uk/kmi-abstracts/kmi-tr-19-abstract.html

[Col97a] Collins, T. D.: Genotypic-Space Mapping: Population Visualization for Genetic Algorithms. Technical Report, KMI-TR-39, Knowledge Media Institure, The Open University, Milton Keynes, UK, 1997.
http://kmi.open.ac.uk/~trevor/research/publications/kmi-tr-39.ps.gz

[Col97b] Collins, T. D.: Using Software Visualization technology to help Genetic Algorithms Designers. In Proceedings of The Ninth Annual Conference of the Psychology of Programming Interest Group (PPIG 9), pp. 43-51, 1997.
http://kmi.open.ac.uk/~trevor/research/publications/PPIG-97.ps.gz

[CC94] Cox, T. F. and Cox, M. A. A.: Multidimensional Scaling. London: Chapman & Hall, 1994.

[DH73] Duda, R. O. and Hart, P. E.: Pattern Classification and Scene Analysis. New York: John Wiley & Sons, 1973.

[DCW96] Dybowski, R., Collins, T. D. and Weller, P. D.: Visualization of binary string convergence by Sammon mapping. in [EP96], pp. 377-383, 1996.
http://kmi.open.ac.uk/~trevor/research/publications/EP96.ps.gz

[JF95] siehe S.

[NEA94] Nassersharif, B., Ence, D. and Au, M.: Visualization of Evolution of Genetic Algorithms, in: Proceedings of World Congress on Neural Networks WCNN'94, San Diego, CA, USA, Hillside, NJ, USA: Lawrence Erlbaum Associates, pp. 1/560-1/565, 1994.

[Poh97] siehe S.

[Rip96] Ripley, B. D.: Pattern Recognition and Neural Networks. Cambridge, GB: Cambridge University Press, 1996.

[RC93] Routen, T. W. and Collins, T. D.: The Visualisation of AI Techniques. Proceedings of Third International Conference on Computational Graphics and Visualisation Techniques COMPUGRAPH'93, Alvor, Portugal, New York, USA: ACM Press, pp. 274-282, 1993

[Rou94] Routen, T. W.: Techniques for the Visualisation of Genetic Algorithms. in [ICEC94] Vol. II, pp. 846-851, 1994.

[Sam69] Sammon, J. W. jr.: A Nonlinear Mapping for Data Structure Analysis. IEEE Transactions on Computers, vol. C-18, no. 5, pp. 401-409, 1969.

[Swm96] siehe S.

9.1.4 Polyploidie bei Evolutionären Algorithmen

[Bag67] Bagley, J. D.: The behavior of adaptive systems which employ genetic and correlation algorithms. Doctoral dissertation, University of Michigan, Dissertation Abstracts International, 28(12), 5106B, University Microfilms No. 68-7556, 1967.

[Bri81] Brindle, A.: Genetic algorithms for function optimization. unpublished doctoral dissertation, University of Alberta: Edmonton, 1981.

[CCR96] Collingwood, E., Corne, D. and Ross, P.: Useful Diversity via Multiploidy. in [AISB96], Workshop Proceedings, pp. 49-53, 1996.

[GS87] Goldberg, D. E. and Smith, R. E.: Nonstationary function optimization using genetic algorithms with dominance and diploidy. in [ICGA2], pp. 59-68, 1987.

[Gol89] siehe S.

[Hol71] Hollstien, R. B.: Artificial genetic adaptation in computer control systems. Doctoral dissertation, University of Michigan, Dissertation Abstracts International, 32(3), 1510B, University Microfilms No. 71-23,773, 1971.

_NW95_ Ng, K. P. and Wong, K. C.: A New Diploid Scheme and Dominance Change Mechanism for Non-Stationary Function Optimization. in [ICGA6], pp. 159-166, 1995.

[Ros67] Rosenberg, R. S.: Simulation of genetic populations with biochemical properties. Doctoral dissertation, University of Michigan, Dissertation Abstracts International, 28(7), 2732B, University Microfilms No. 67-17,836, 1967.

[Rya96] Ryan, C.: Reducing Premature Convergence in Evolutionary Algorithms. Ph.D. thesis, University College Cork, Ireland, 1996.
ftp://odyssey.ucc.ie/pub/genetic/thesis.ps.Z

[Smi87] Smith, R. E.: Diploid genetic algorithms for search in time varying environments. Proceedings of the 25th Annual Southeast Regional Conference of the ACM, pp. 175-178, 1987.

[Smi88] Smith, R. E.: An investigation of diploid genetic algorithms for adaptive search of nonstationary functions. Unpublished master's thesis, University of Alabama: Tuscaloosa, 1988.

_YA94_ Yoshida, Y. and Adachi, N.: A Diploid Genetic Algorithm for Preserving Population Diversity - pseudo-Meiosis GA. in [PPSN3], pp. 36-45, 1994.

9.1.5 Biologie, Genetik und Populationsgenetik

[CK70] Crow, J. F. and Kimura, M.: An Introduction to Population Genetics Theory. New York: Harper and Row, 1970.

[Dar1859] Darwin, C.: On the origin of species by means of natural selection. London: Murray, 1859.
(Deutsche Übersetzung: Die Entstehung der Arten durch natürliche Zuchtwahl. 1860.
Stuttgart: Reclam, 1974.)

[Fwb63] Fremdwörterbuch. Leipzig: Bibliographisches Institut, 1963.

[Hag91] Hagemann, R.: Allgemeine Genetik. Jena: Gustav Fischer Verlag, 1991.

[Ode97] Odenbach, W.: Biologische Grundlagen der Pflanzenzüchtung. Berlin: Parey Buchverlag, 1997.

[Hen95] Hennig, W.: Genetik. Berlin, Heidelberg: Springer-Verlag, 1995.

[RM54] Rieger, R. and Michaelis, A.: Genetisches und Cytogenetisches Wörterbuch. Der Züchter, 2. Sonderheft, Berlin, Göttingen, Heidelberg: Springer-Verlag, 1954.

[Wer68] Werner, F.: Wortelemente lateinisch-griechischer Fachausdrücke in den biologischen Wissenschaften. Halle (Saale): Max Niemeyer Verlag, 1968.

9.1.6 Pflanzenwachstum und Gewächshaus

[Als93] Alscher, G.: Optimierung der CO₂- und Temperaturregelung bei Gewächshauskulturen mit Hilfe von Modellansätzen unterschiedlicher Abstraktionsebenen. Dissertation, Universität Hannover, 1993.

[Arn87] Arnold, E.: Zur optimalen Steuerung zeitdiskreter dynamischer Prozesse mittels nichtlinearer Optimierung mit Anwendungen auf die Klimasteuerung von Gewächshäusern. Dissertation, Technische Hochschule Ilmenau, 1987.

[BC94] Bailey, B. J. and Chalabi, Z. S.: Improving the cost effectiveness of greenhouse climate control. in Computers and Electronics in Agriculture 10 (1994), pp. 203-214, 1994.

[CBW96] Chalabi, Z. S., Bailey, B. J. and Wilkinson, D. J.: A real-time optimal control algorithm for greenhouse heating. in Computers and Electronics in Agriculture 15 (1996), pp. 1-13, 1996.

[DY96] Day, W. and Young, P. C.: Proceedings of the Second IFAC/ISHS Workshop on Mathematical and Control Applications in Agriculture and Horticulture. Acta Horticulturae, 406, 1996.

[Hei96] Heißner, A.: Ein einfaches Gewächshausklimamodell für die Kurzfriststeuerung von Temperatur, Luftfeuchte und CO₂-Konzentration. Gartenbauwissenschaft, 61 (6), pp. 289-300, 1996.

[Hei97] Heißner, A.: Der CO₂-Gaswechsel von Paprikapflanzen in Abhängigkeit von der Bestrahlungsstärke, der CO₂-Konzentration, der Lufttemperatur und dem Dampfdrucksättigungsdefizit der Luft: Messungen und Modell. Gartenbauwissenschaft, 62 (2), pp. 78-90, 1997.

[JHS95] Jones, J. W., Hwang, Y. K. and Seginer, I.: Simulation of Greenhouse Crops, Environments and Control Systems. Acta Horticulturae, 399, pp. 73-84, 1995.

[Mar90] Markert, A.: Aggregation pflanzenphysiologischer Wachstumsmodelle und Berechnung von Steuerstrategien für das Gewächshausinnenklima mittels Verfahren der nichtlinearen Optimierung. Dissertation, Technische Hochschule Ilmenau, 1990.

[Mat95] Matitschka, G.: Vereinfachende Beschreibung der Bruttophotosynthese des physiologisch-dynamischen Simulationsmodells SUCROS und Weiterentwicklung für spezielle Anwendungen im Gemüsebau (Produktionssysteme Kohlrabi und Kopfsalat). Dissertation, Universität Hohenheim, Stuttgart: Verlag Ulrich E. Grauert, 1995.

[PH96a] siehe S.

[PH96b] siehe S.

[PH96c] siehe S.

[PH97a] siehe S.

[PH97b] siehe S.

[Sch85] Schmidt, M.: Bestimmung optimaler klimatischer Wachstumsfaktoren von Gewächshauskulturen auf der Basis pflanzenphysiologischer Beschreibungsmodelle. Dissertation, Technische Hochschule Ilmenau, 1985.

[Seg96] Seginer, I.: Optimal control of the greenhouse environment. in [DY96], pp. 191-202, 1996.

[vSC95] van Straten, G. and Challa, H.: Greenhouse climate control systems. in Bakker, J. C., Bot, G. P. A., Challa, H. and Van de Braak, N. J. (ed.): Greenhouse climate control - an integrated approach. Wageningen: Wageningen Press, 1995.

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