Publications

• Books
  1. G. Rudolph: Convergence Properties of Evolutionary Algorithms, Hamburg: Kovac 1997, ISBN 3-86064-554-4.

• Edited Books
  1. M. Schoenauer, K. Deb, G. Rudolph, X. Yao, E. Lutton, J.J. Merelo, and H.-P. Schwefel (eds.): Proceedings of the 6th International Conference on Parallel Problem Solving from Nature - PPSN VI, Berlin and Heidelberg: Springer 2000.
  2. W. B. Langdon, E. Cantu-Paz, K. Mathias, R. Roy, D. Davis, R. Poli, K. Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M. A. Potter, A. C. Schulz, J. F. Miller, E. Burke, and N. Jonoska (eds.): Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002), San Francisco (CA): Morgan Kaufmann Publishers 2002.
  3. T. Bartz-Beielstein, G. Jankord, B. Naujoks, G. Rudolph, and K. Schmitt (eds.): Festschrift Hans-Paul Schwefel 2006, Universität Dortmund, Dortmund 2006 (ISBN 3-921823-34-X).
  4. T. Bartz-Beielstein, M.J. Blesa Aguilera, C. Blum, B. Naujoks, A. Roli, G. Rudolph, M. Samples (eds.): Hybrid Metaheuristics, Proceedings of the 4th International Workshop (HM 2007), Lecture Notes in Computer Science Vol. 4771, Springer: Berlin and Heidelberg 2007.
  5. G. Rudolph, T. Jansen, S. Lucas, C. Poloni, and N. Beume (eds.): Proceedings of the 10th International Conference on Parallel Problem Solving from Nature - PPSN X, Lecture Notes in Computer Science Vol. 5199, Springer: Berlin and Heidelberg 2008.
  6. R. Schaefer, C. Cotta, J. Kolodziej, and G. Rudolph (eds.): Proceedings of the 11th International Conference on Parallel Problem Solving from Nature - PPSN XI, Lecture Notes in Computer Science Vol. 6238 & 6239, Springer: Berlin and Heidelberg 2010.

• Journals
  1. G. Rudolph: Massively Parallel Simulated Annealing and its Relation to Evolutionary Algorithms, Evolutionary Computation 1(4):361-382, 1994.
  2. G. Rudolph: Convergence Properties of Canonical Genetic Algorithms, IEEE Transactions on Neural Networks 5(1):96-101, 1994.
  3. G. Rudolph and H.-P. Schwefel: Evolutionäre Algorithmen: Ein robustes Optimierkonzept, Physikalische Blätter 50(3):236-238, 1994.
  4. G. Yin, G. Rudolph, and H.-P. Schwefel: Establishing connections between evolutionary algorithms and stochastic approximation, Informatica 6(1):93-116, 1995.
  5. G. Yin, G. Rudolph, and H.-P. Schwefel: Analyzing (1,lambda) Evolution Strategy via Stochastic Approximation Methods, Evolutionary Computation 3(4):473-489, 1996.
  6. G. Rudolph: How Mutation and Selection Solve Long Path-Problems in Polynomial Expected Time, Evolutionary Computation 4(2):195-205, 1997.
  7. G. Rudolph: Convergence Rates of Evolutionary Algorithms for a Class of Convex Objective Functions, Control and Cybernetics 26(3):375-390, 1997.
  8. G. Rudolph: Local Convergence Rates of Simple Evolutionary Algorithms with Cauchy Mutations, IEEE Transactions on Evolutionary Computation 1(4):249-258, 1997.
  9. G. Rudolph: Finite Markov Chain Results in Evolutionary Computation: A Tour d'Horizon, Fundamenta Informaticae 35(1-4):67-89, 1998.
  10. A. E. Eiben and G. Rudolph: Theory of Evolutionary Algorithms: A Bird's Eye View, Theoretical Computer Science 229(1):3-9, 1999.
  11. G. Rudolph: Self-Adaptive Mutations May Lead to Premature Convergence, IEEE Transactions on Evolutionary Computation 5(4):410-414, 2001.
  12. K. Weinert, J. Mehnen, and G. Rudolph: Dynamic Neighborhood Structures in Parallel Evolution Strategies, Complex Systems 13(3):227-243, 2001.
  13. G. Rudolph: Analysis of a Non-Generational Mutationless Evolutionary Algorithm for Separable Fitness Functions, International Journal of Computational Intelligence Research 1(1):77-84, 2005.
  14. R. Klinger and G. Rudolph: Automatic Composition of Music with Methods of Computational Intelligence, WSEAS Transactions on Information Science & Applications 4(3):508-517, 2007.
  15. F. Henrich, C. Bouvy, Ch. Kausch, K. Lucas, M. Preuß, G. Rudolph, and P. Roosen: Economic optimization of non-sharp separation sequences by means of evolutionary algorithms, Computers and Chemical Engineering 32(7):1411-1432, 2008
  16. N. Beume, B. Naujoks, and G. Rudolph: SMS-EMOA: Effektive evolutionäre Mehrzieloptimierung, Automatisierungstechnik (at) 56(7):357-364, 2008.
  17. Zhiyong Li, G. Rudolph, and Kenli Li: Convergence performance comparison of quantum-inspired multi-objective evolutionary algorithms, Computers and Mathematics with Applications 57(11/12):1843-1854, 2009.
  18. H. Blume, B. Bischl, M. Botteck, C. Igel, R. Martin, G. Rötter, G. Rudolph, W. Theimer, I. Vatolkin, and C. Weihs: Huge Music Archives on Mobile Devices, IEEE Signal Processing Magazine 28(4):24-39, 2011.

• Contributions to edited works (not available online, sorry!)
  1. G. Rudolph: Evolution Strategies, pp. B1.3.1-6, in T. Bäck, D.B. Fogel, and Z. Michalewicz (eds.): Handbook of Evolutionary Computation, IOP Publishing and Oxford University Press: Bristol and New York 1997.
     Also published on pp. 81-88 in T. Bäck et al. (eds): Evolutionary Computation 1 - Basic Algorithms and Operators, IOP Publishing; Bristol 2000.
  2. G. Rudolph: Stochastic Processes, pp. B2.2.1-8, in T. Bäck, D.B. Fogel, and Z. Michalewicz (eds.): Handbook of Evolutionary Computation, IOP Publishing and Oxford University Press: Bristol and New York 1997.
  3. G. Rudolph: Modes of Stochastic Convergence, pp. B2.3.1-3, in T. Bäck, D.B. Fogel, and Z. Michalewicz (eds.): Handbook of Evolutionary Computation, IOP Publishing and Oxford University Press: Bristol and New York 1997.
  4. G. Rudolph: Local Performance Measures: Genetic Algorithms, pp. B2.4.20-27, in T. Bäck, D.B. Fogel, and Z. Michalewicz (eds.): Handbook of Evolutionary Computation, IOP Publishing and Oxford University Press: Bristol and New York 1997.
  5. G. Rudolph and J. Ziegenhirt: Computation time of evolutionary operators, pp. E2.2.1-4, in T. Bäck, D.B. Fogel, and Z. Michalewicz (eds.): Handbook of Evolutionary Computation, IOP Publishing and Oxford University Press: Bristol and New York 1997.
     Also published on pp. 247-252 in T. Bäck et al. (eds): Evolutionary Computation 2 - Advanced Algorithms and Operators, IOP Publishing; Bristol 2000.
  6. S. Droste, Th. Jansen, G. Rudolph H.-P. Schwefel, K. Tinnefeld, and I.Wegener: Theory of evolutionary algorithms and genetic programming, pp. 107-144 in H.-P. Schwefel, I. Wegener und K. Weinert (eds.): Advances in Computational Intelligence. Springer, Berlin und Heidelberg 2003.
  7. G. Rudolph: Parallel Evolution Strategies, pp. 155-169 in E. Alba (ed.): Parallel Metaheuristics: A New Class of Algorithms. Wiley: Hoboken (NJ) 2005.
  8. G. Rudolph: A Time Travel to the Early Theory of Evolution Strategies, pp. 85-89 in T. Bartz-Beielstein et al. (eds.): Festschrift Hans-Paul Schwefel 2006, University of Dortmund, Dortmund 2006 (ISBN 3-921823-34-X).
  9. G. Rudolph and H.-P. Schwefel: Simulated Evolution under Multiple Criteria Revisited, pp. 248-260 in J.M. Zurada et al. (eds.): WCCI 2008 Plenary/Invited Lectures, Springer: Berlin 2008.
  10. E.-G. Talbi, S. Monastghim, T. Okabe, H. Ishibuchi, G. Rudolph, and C.A. Coello Coello: Parallel Approaches for Multiobjective Optimization, pp. 349-372 in J. Branke et al. (eds): Multiobjective Optimization - Interactive and Evolutionary Approaches, Springer: Berlin 2008.
  11. G. Rudolph: Evolutionary Strategies. In G. Rozenberg, T. Bäck, and J.N. Kok (eds.): Handbook of Natural Computing. Springer, to appear 2012.
  12. G. Rudolph: Stochastic Convergence. In G. Rozenberg, T. Bäck, and J.N. Kok (eds.): Handbook of Natural Computing. Springer, to appear 2012.

• Proceedings
  1. G. Rudolph: Global Optimization by Means of Distributed Evolution Strategies, pp. 209-213 in H.-P. Schwefel and R. Männer (eds.): Parallel Problem Solving from Nature, Berlin: Springer 1991.
  2. G. Rudolph: Parallel Approaches to Stochastic Global Optimization, pp. 256-267 in W. Joosen and E. Milgrom (eds.): Parallel Computing: From Theory to Sound Practice, Proceedings of the European Workshop on Parallel Computing (EWPC 92), Amsterdam: IOS Press 1992.
  3. G. Rudolph: On Correlated Mutations in Evolution Strategies, pp. 105-114 in: R. Männer and B. Manderick: Parallel Problem Solving from Nature, 2. Amsterdam: Elsevier 1992.
  4. G. Rudolph: Parallel Clustering on a Unidirectional Ring, pp. 487-493 in R. Grebe et al. (eds.): Transputer Applications and Systems '93; Vol. 1, Amsterdam: IOS Press 1993.
  5. Th. Bäck, G. Rudolph, and H.-P. Schwefel: Evolutionary Programming and Evolution Strategies: Similarities and Differences, pp. 11-22 in D.B. Fogel and W. Atmar (eds.): Proceedings of the 2nd Annual Conference on Evolutionary Programming, La Jolla, CA: Evolutionary Programming Society 1993.
  6. G. Rudolph: Convergence of Non-Elitist Strategies, pp. 63-66 in: Proceedings of the First IEEE Conference on Evolutionary Computation, Vol. 1, Piscataway, NJ: IEEE Press 1994.
  7. G. Rudolph: An Evolutionary Algorithm for Integer Programming, pp. 139-148 in Y. Davidor, H.-P. Schwefel, and R. Männer (eds.): Parallel Problem Solving From Nature, 3. Berlin: Springer 1994.
  8. H.-P. Schwefel and G. Rudolph: Contemporary Evolution Strategies, pp. 893-907 in F. Morana et al. (eds.): Advances in Artificial Life. Berlin: Springer 1995. (revised version)
  9. G. Rudolph and J. Sprave: A cellular genetic algorithm with self-adjusting acceptance threshold, pp. 365-372 in Proceedings of the First IEE/IEEE International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, London: IEE Press 1995.
  10. G. Rudolph and J. Sprave: Significance of Locality and Selection Pressure in the Grand Deluge Evolutionary Algorithm, pp. 686-695 in H.-M. Voigt et al. (eds.): Parallel Problem Solving From Nature - PPSN IV. Berlin: Springer 1996.
  11. G. Rudolph: On interactive evolutionary algorithms and stochastic Mealy automata, pp. 218-226 in H.-M. Voigt et al. (eds.): Parallel Problem Solving From Nature - PPSN IV. Berlin: Springer 1996.
  12. G. Rudolph: Convergence of Evolutionary Algorithms in General Search Spaces, pp. 50-54 in: Proceedings of the Third IEEE Conference on Evolutionary Computation, Piscataway, NJ: IEEE Press 1996.
      Best paper award.
  13. M. Höhfeld and G. Rudolph: Towards a Theory of Population-Based Incremental Learning, pp. 1-5 in: Proceedings of the 4th IEEE Conference on Evolutionary Computation, Piscataway, NJ: IEEE Press 1997.
  14. G. Rudolph: Reflections on Bandit Problems and Selection Methods in Uncertain Environments, pp. 166-173 in T. Bäck (ed.): Proceedings of the 7th International Conference on Genetic Algorithms (ICGA '97), San Francisco, CA: Morgan Kaufmann 1997.
  15. G. Rudolph: Asymptotical Convergence Rates of Simple Evolutionary Algorithms under Factorizing Mutation Distributions, pp. 223-233 in: J.K. Hao, E. Lutton, E. Ronald, M. Schoenauer, and D. Snyers (eds.): Proceedings of Artificial Evolution '97, Berlin: Springer 1998.
  16. G. Rudolph: Evolutionary Search for Minimal Elements in Partially Ordered Finite Sets, pp. 345-353 in V.W. Porto, N. Saravanan, D. Waagen, and A.E. Eiben (eds.): Evolutionary Programming VII, Proceedings of the 7th Annual Conference on Evolutionary Programming, Berlin: Springer 1998.
  17. G. Rudolph: On a Multi-Objective Evolutionary Algorithm and Its Convergence to the Pareto Set, pp. 511-516 in: Proceedings of the 5th IEEE Conference on Evolutionary Computation, IEEE Press, Piscataway (NJ) 1998.
  18. G. Rudolph: On Risky Methods for Local Selection under Noise, pp. 169-177 in Th. Bäck, A.E. Eiben, M. Schoenauer, and H.-P. Schwefel (eds.): Parallel Problem Solving From Nature - PPSN V, Berlin: Springer 1998.
  19. M. Laumanns, G. Rudolph, and H.-P. Schwefel: A Spatial Predator-Prey Approach to Multi-Objective Optimization: A Preliminary Study, pp. 241-249 in Th. Bäck, A.E. Eiben, M. Schoenauer, and H.-P. Schwefel (eds.): Parallel Problem Solving From Nature - PPSN V, Berlin: Springer 1998.
  20. G. Rudolph: Self-Adaptation and Global Convergence: A Counter-Example, pp. 646-651 in: Proceedings of the Congress on Evolutionary Computation (CEC'99), Vol. 1, IEEE Press, Piscataway (NJ) 1999. (revised version)
  21. G. Rudolph: On Takeover Times in Spatially Structured Populations: Array and Ring, pp. 144-151 in K. K. Lai, O. Katai, M. Gen, and B. Lin (eds.): Proceedings of the 2nd Asia-Pacific Conference on Genetic Algorithms and Applications, Hong Kong: Global-Link Publishing Company 2000.
  22. G. Rudolph: Takeover Times and Probabilities of Non-Generational Selection Rules, pp. 903-910 in D. Whitley et al. (eds.): Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2000), San Francisco (CA): Morgan Kaufmann 2000.
  23. G. Rudolph and A. Agapie: Convergence Properties of Some Multi-Objective Evolutionary Algorithms, pp. 1010-1016 in A. Zalzala et al. (eds.): Proceedings of the 2000 Congress on Evolutionary Computation (CEC 2000), Vol. 2, IEEE Press, Piscataway (NJ) 2000.
  24. G. Rudolph: Some Theoretical Properties of Evolutionary Algorithms under Partially Ordered Fitness Values, pp. 9-22 in Cs. Fabian and I. Intorsureanu (eds.): Proceedings of the Evolutionary Algorithms Workshop (EAW-2001), Bucharest, Romania, January 2001.
  25. G. Rudolph: Evolutionary Search under Partially Ordered Fitness Sets, pp. 818-822 in M.F. Sebaaly (ed.): Proceedings of the International NAISO Congress on Information Science Innovations (ISI 2001), ICSC Academic Press: Millet/Sliedrecht 2001. (ISBN 3-906454-25-8)
  26. G. Rudolph: Takeover Times of Noisy Non-Generational Selection Rules that Undo Extinction, pp. 268-271 in V. Kurkova et al. (eds.): Proceedings of the 5th International Conference on Artificial Neural Nets and Genetic Algorithms (ICANNGA 2001), Springer, Vienna 2001.
  27. G. Rudolph: A Partial Order Approach to Noisy Fitness Functions, pp. 318-325 in: J.-H. Kim, B.-T. Zhang, G. Fogel, and I. Kuscu (eds.): Proceedings of the 2001 IEEE Congress on Evolutionary Computation (CEC 2001), IEEE Press, Piscataway (NJ) 2001.
  28. M. Laumanns, G. Rudolph, and H.-P. Schwefel: Mutation Control and Convergence in Evolutionary Multi-Objective Optimization, pp. 24-29 in R. Matousek and P. Osmera (eds.): Proceedings of the 7th International Conference on Soft Computing (MENDEL 2001), Brno University of Technology, Brno, Czech Republic, 2001. (ISBN 80-214-1894-X)
  29. F. Hoffmann, T. Nierobisch, T. Seyffarth, and G. Rudolph: Visual Servoing with Moments of SIFT Features, pp. 4262-4267 in: Proceedings of the 2006 IEEE Conference on Systems, Man, and Cybernetics (IEEE SMC 2006), IEEE Press: Piscataway (NJ) 2006.
  30. M. Preuss, B. Naujoks, and G. Rudolph: Pareto Set and EMOA Behavior for Simple Multimodal Multiobjective Functions, pp. 513-522 in: T.P. Runarsson et al. (eds): Proceedings of the Ninth International Conference on Parallel Problem Solving from Nature (PPSN IX), Springer, Berlin 2006.
  31. G. Rudolph: Takeover Time in Parallel Populations with Migration, pp. 63-72 in: B. Filipic and J. Silc (eds.): Proceedings of the Second International Conference on Bioinspired Optimization Methods and their Applications (BIOMA 2006), Josef Stefan Institute: Ljubljana 2006.
  32. G. Rudolph: Deployment Scenarios of Parallelized Code in Stochastic Optimization, pp. 3-11 in: B. Filipic and J. Silc (eds.): Proceedings of the Second International Conference on Bioinspired Optimization Methods and their Applications (BIOMA 2006), Josef Stefan Institute: Ljubljana 2006. (Remark: invited paper)
  33. J. Mehnen, T. Wagner, and G. Rudolph: Evolutionary Optimization of Dynamic Multi-objective Test Functions , in: Proceedings of the Second Italian Workshop on Evolutionary Computation (GSICE2), September 2006, Siena (Italy), published on CD-ROM.
  34. T. Bartz-Beielstein, M. Preuss, and G. Rudolph: Investigation of One-Go Evolution Strategy/Quasi-Newton Hybridizations, pp. 178-191 in: F. Almeida et al. (eds.): Proceedings of the Third International Workshop on Hybrid Metaheuristics (HM 2006), Springer: Berlin 2006.
  35. N. Beume and G. Rudolph: Faster S-Metric Calculation by Considering Dominated Hypervolume as Klee's Measure Problem, pp. 231-236 in: B. Kovalerchuk (ed.): Proceedings of the Second IASTED Conference on Computational Intelligence, ACTA Press: Anaheim 2006.
      Extended version: Technical Report CI-216/06, SFB 531, University of Dortmund, June 2006.
  36. R. Klinger and G. Rudolph: Evolutionary Composition of Music with Learned Melody Evaluation, pp. 234-239 in N. Mastorakis and A. Cecchi (Eds.): Proceedings of the 5th WSEAS Int. Conf. on Computational Intelligence, Man-Machine Systems and Cybernetics, 2006.
      Best student paper award (R. Klinger).
  37. N. Beume, B. Naujoks, and G. Rudolph: Mehrkriterielle Optimierung durch evolutionäre Algorithmen mit S-Metrik-Selektion, pp. 1-10 in: R. Mikut and M. Reischl (eds.): Proceedings of the 16th GMA Workshop Computational Intelligence, Universitätsverlag Karlsruhe, 2006.  
      Young researcher award (N. Beume).
  38. G. Rudolph, B. Naujoks, and M. Preuss: Capabilities of MOEA to Detect and Preserve Equivalent Pareto Subsets, pp. 36-50 in S. Obayashi et al. (eds.): Proceedings of the 4th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2007), Springer: Berlin 2007.
  39. M. Preuss, G. Rudolph, and F. Tumakaka: Solving Multimodal Problems via Multiobjective Techniques with Application to Phase Equilibrium Detection, pp. 2703-2710 in K.C. Tan et al. (eds.): Proceedings of the 2007 IEEE Congress on Evolutionary Computation, IEEE Press: Piscataway (NJ) 2007.
  40. G. Rudolph and M. Preuss: Ein mehrkriterielles Evolutionsverfahren zur Bestimmung des Phasengleichgewichts von gemischten Flüssigkeiten, pp. 177-185 in R. Mikut and M. Reischl (eds.): Proceedings of the 17th GMA Workshop on Computational Intelligence, Universitätsverlag Karlsruhe 2007. ISBN 978-3-86644-191-0  
  41. Zhiyong Li, Zhe Li, and G. Rudolph: On the Convergence Properties of Quantum-Inspired Multi-Objective Evolutionary Algorithms, pp. 245-255 in D.-S. Huang, L. Heutte, and M. Loog (eds.): Proceedings of the International Conference on Intelligent Computing (ICIC 2007), Springer: Berlin 2007.
  42. M. Sathe, G. Rudolph, and K. Deb: Design and Validation of a Hybrid Interactive Reference Point Methods for Multi-Objective Optimization, pp. 2914-2921 in Proceedings of the 2008 IEEE Congress on Evolutionary Computation, IEEE Press: Piscataway (NJ) 2008.
  43. T. Voß, N. Beume, G. Rudolph, and C. Igel: Scalarization versus Indicator-based Selection in Multi-Objective CMA Evolution Strategies. pp. 3041-3048 in Proceedings of the 2008 IEEE Congress on Evolutionary Computation, IEEE Press: Piscataway (NJ) 2008.
  44. G. Rudolph and M. Preuss: Ein Evolutionsverfahren zur Approximation äquivalenter Urbilder von Pareto-optimalen Zielvektoren, pp. 30-39 in R. Mikut and M. Reischl (eds.): Proceedings of the 18th GMA Workshop on Computational Intelligence, Universitätsverlag Karlsruhe 2008.
  45. N. Beume, B. Naujoks, M. Preuss, G. Rudolph, and T. Wagner: Effects of 1-Greedy S-Metric-Selection on Innumerably Large Pareto Fronts, pp. 21-35 in M. Ehrgott et al. (eds.): Proceedings of 5th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2009), Springer: Berlin and Heidelberg 2009.
  46. G. Rudolph and M. Preuss: A Multiobjective Approach for Finding Equivalent Inverse Images of Pareto-optimal Objective Vectors, pp. 74-79 in C. Coello Coello, P.P. Bonissone, and Y. Jin (ed.): 2009 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (IEEE MCDM 2009), IEEE Press: Piscataway (NJ) 2009.
  47. I. Vatolkin, W. Theimer, and G. Rudolph: Design and Comparison of Different Evolution Strategies for Feature Selection and Consolidation in Music Classification, pp. 174-181 in Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC 2009), IEEE Press: Piscataway (NJ) 2009.
  48. P. Koch, O. Kramer, G. Rudolph, and N. Beume: On the Hybridization of SMS-EMOA and Local Search for Multiobjective Continuous Optimization, pp. 603-610 in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2009), ACM Press: New York 2009.
  49. O. Kramer, A. Barthelmes, and G. Rudolph: Surrogate Constraint Functions for CMA Evolutions Strategies, pp. 169-178 in B. Mertsching et al. (eds.): KI 2009 - Advances in Artificial Intelligence. Proceedings of the 32nd Annual Conference on Artificial Intelligence, LNAI 5803, Springer: Berlin and Heidelberg 2009.
  50. M. Preuss, G. Rudolph, and S. Wessing: Tuning Optimization Algorithms for Real-World Problems by Means of Surrogate Modeling, pp. 401-408 in M. Pelikan and J. Branke (Eds.): Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2010), ACM Press: New York 2010.
  51. J. Quadflieg, M. Preuss, O. Kramer, and G. Rudolph: Learning the Track and Planning Ahead in a Car Racing Controller, pp. 395-402 in Proceedings of the IEEE Symposium on Computational Intelligence and Games (CIG 2010), IEEE Press: Piscataway (NJ) 2010.
  52. N. Beume, M. Laumanns, and G. Rudolph: Convergence Rates of (1+1) Evolutionary Multiobjective Algorithms, pp. 597-606 in R. Schaefer et al. (Eds.): Proceedings of the 11th Int'l Conf. on Parallel Problem Solving from Nature (PPSN XI), Springer: Berlin 2010.
  53. S. Wessing, N. Beume, G. Rudolph, and B. Naujoks: Parameter Tuning Boosts Performance of Variation Operators in Multiobjective Optimization, pp. 728-737 in R. Schaefer et al. (Eds.): Proceedings of the 11th Int'l Conf. on Parallel Problem Solving from Nature (PPSN XI), Springer: Berlin 2010.
  54. N. Beume, M. Laumanns, and G. Rudolph: Convergence Rates of SMS-EMOA on Continuous Bi-Objective Problem Classes, pp.243-251 in H.-G. Beyer and W. B. Langdon (Eds.): Proceedings of the 11th Int'l Conf. on Foundations of Genetic Algorithms (FOGA XI), ACM Press: New York 2011.
  55. J. Quadflieg, M. Preuss, and G. Rudolph: Driving Faster Than a Human Player, pp. 143-152 in C. Di Chio et al. (Eds.): Proceedings of Int'l Conf. on Applications of Evolutionary Computation (EvoApplications), part 1, Springer: Berlin 2011.
  56. G. Rudolph: On Geometrically Fast Convergence to Optimal Dominated Hypervolume of Set-based Multiobjective Evolutionary Algorithms, pp. 1718-1722 in A. Smith (ed.): Proceedings of 2011 IEEE Congress on Evolutionary Computation (CEC 2011), IEEE Press: Piscataway (NJ) 2011.
  57. F. Neumann, P. Oliveto, G. Rudolph, and D. Sudholt: On the Effectiveness of Crossover for Migration in Parallel Evolutionary Algorithms, pp. 1587-1594 in N. Krasnogor and P.L. Lanzi (eds.): Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2011), ACM Press: New York 2011.
  58. M. Preuss, G. Rudolph, and I. Vatolkin: Multi-Objective Feature Selection in Music Genre and Style Recognition Tasks, pp. 411-418 in N. Krasnogor and P.L. Lanzi (eds.): Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2011), ACM Press: New York 2011.
  59. M. Preuss, S. Wessing, and G. Rudolph: When Parameter Tuning Actually is Parameter Control, pp. 821-828 in N. Krasnogor and P.L. Lanzi (eds.): Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2011), ACM Press: New York 2011.
  60. O. Mersmann, B. Bischl, H. Trautmann, M. Preuss, C. Weihs, and G. Rudolph: Exploratory Landscape Analysis, pp. 829-836 in N. Krasnogor and P.L. Lanzi (eds.): Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2011), ACM Press: New York 2011.
  61. T. Deinert, I. Vatolkin, and G. Rudolph: Regression-Based Tempo Recognition from Chroma and Energy Accents for Slow Audio Recordings, pp. 60-68 in K. Brandenburg and M. Sandler (eds.): Proceedings of AES 42nd Int'l Conf. on Semantic Audio, Audio Engineering Society: New York 2011.
  62. K. Gerstl, G. Rudolph, O. Schütze, and H. Trautmann: Finding Evenly Spaced Fronts for Multiobjective Control via Averaging Hausdorff-Measure, accepted at 8th International Conference on Electrical Engineering, Computer Science and Automatic Control (CCE 2011), Mérida (Mexico), October 26-28, 2011.

• Work currently under review

  some

• Miscellaneous
  1. M. Laumanns, G. Rudolph, and H.-P. Schwefel: Adaptive Mutation Control in Panmictic And Spatially Distributed Multi-objective Evolutionary Algorithms, PPSN/SAB Workshop on Multiobjective Problem Solving from Nature (MPSN), Paris, September 2000.
  2. Z. Li and G. Rudolph: A Framework of Quantum-inspired Multi-Objective Evolutionary Algorithms and its Convergence Condition, Accepted for poster presentation at GECCO 2007, London (UK), July 2007.
  3. B. Künne, G. Rudolph, B. Naujoks, T. Richard, B. Schultebraucks: A multiobjective evolutionary algorithm for designing and optimizing gearshafts. pp. 267-268 in P. Scharff (ed.): 53. Internationales Wissenschaftliches Kolloquium (IWK) der TU Ilmenau (Proceedings CD-Rom), ISLE, TU Ilmenau 2008 (ISBN 978-3-938843-40-6).
  4. G. Rudolph: The Virtues of Metaheuristics in Stochastic Programming, pp. 55-57 in A. Borkowski and M. Nagl (eds.): Abstracts of the 1st Polish-German Workshop on Research Co-operation in Computer Science. Polish Academy of Science, Warsaw 2009 (ISBN 978-83-924901-7-3).
  5. G. Rudolph, M. Preuss, and J. Quadflieg: Double-layered Surrogate Modeling for Tuning Metaheuristics, presented at ENBIS/EMSE Conference "Design and Analysis of Computer Experiments", Saint-Etienne (France), July 1-3, 2009.
     Available as Technical Report.

• Unpublished
  1. M. Laumanns, G. Rudolph, and H.-P. Schwefel: Approximating the Pareto Set: Concepts, Diversity Issues, and Performance Assessment. Technical Report CI-72/99, University of Dortmund, March 1999 (ISSN 1433-3325).
  2. G. Rudolph: The Fundamental Matrix of the General Random Walk with Absorbing Boundaries. Technical Report CI-75/99, University of Dortmund, October 1999 (ISSN 1433-3325).