Mike Preuss  •  Algorithm Engineering  •  TU Dortmund
	Publikationen

meine Veröffentlichungen (nur diejenigen, die unter Peer Review standen) in umgekehrter chronologischer Reihenfolge:

2009:

R. Stoean, M. Preuss, C. Stoean, E. El-Darzi, and D. Dumitrescu. An evolutionary approximation for the coefficients of decision functions within a support vector machine learning strategy. In A. E. Hassanien and A. Abraham, editors, Foundations of Computational, Intelligence Volume 1, volume 201/2009 of Studies in Computational Intelligence, pages 315-347. Springer, 2009. [ bib | DOI ]

R. Stoean, M. P. C. Stoean, E. E-Darzi, and D. Dumitrescu. Support vector machine learning with an evolutionary engine. Journal of the Operational Research Society, 60(8):1116-1122, 2009. [ bib | DOI ]

O. M. Shir, M. Preuss, B. Naujoks, and M. T. M. Emmerich. Enhancing decision space diversity in evolutionary multiobjective algorithms. In M. Ehrgott, C. M. Fonseca, X. Gandibleux, J.-K. Hao, and M. Sevaux, editors, Evolutionary Multi-Criterion Optimization, 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings, volume 5467 of Lecture Notes in Computer Science, pages 95-109. Springer, 2009. [ bib ]

N. Beume, B. Naujoks, M. Preuss, G. Rudolph, and T. Wagner. Effects of 1-greedy -metric-selection on innumerably large pareto fronts. In M. Ehrgott, C. M. Fonseca, X. Gandibleux, J.-K. Hao, and M. Sevaux, editors, Evolutionary Multi-Criterion Optimization, 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings, volume 5467 of Lecture Notes in Computer Science, pages 21-35. Springer, 2009. [ bib ]

M. Preuss. Adaptability of algorithms for real-valued optimization. In M. Giacobini et al., editors, Applications of Evolutionary Computing, EvoWorkshops 2009. Proceedings, volume 5484 of Lecture Notes in Computer Science, pages 665-674, Berlin, 2009. Springer. (Evonum'09 best paper award). [ bib ]

G. Rudolph and M. Preuss. A multiobjective approach for finding equivalent inverse images of pareto-optimal objective vectors. In C. Coello Coello, P. Bonissone, and Y. Jin, editors, 2009 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (IEEE MCDM 2009), pages 74-79, Piscataway (NJ), 2009. IEEE Press. [ bib ]

2008:

C. S. R. Stoean, M. Preuss. Approximating the number of attraction basins of a function by means of clustering and evolutionary algorithms. In 8th International Conference on Artificial Intelligence and Digital Communications (AIDC 2008), pages 171-180, Craiova, Romania, 2008. Research Notes in Artificial Intelligence and Digital Communications, N. Tandareanu (Ed.), Reprograph Press. [ bib ]

N. Beume, T. Hein, B. Naujoks, N. Piatkowski, M. Preuss, and S. Wessing. Intelligent Anti-Grouping in Real-Time Strategy Games. In Proc. of the IEEE Symposium on Computational Intelligence and Games (CIG 2008), pages 71-78, Piscataway NJ, 2008. IEEE Press. [ bib ]

H. Danielsiek, R. Stüer, A. Thom, N. Beume, B. Naujoks, and M. Preuss. Intelligent Moving of Groups in Real-Time Strategy Games. In Proc. of the IEEE Symposium on Computational Intelligence and Games (CIG 2008), pages 63-70, Piscataway NJ, 2008. IEEE Press. [ bib ]

N. Beume, H. Danielsiek, C. Eichhorn, B. Naujoks, M. Preuss, K. Stiller, and S. Wessing. Measuring Flow as Concept for Detecting Game Fun in the Pac-Man Game. In Proc. 2008 Congress on Evolutionary Computation (CEC'08) within Fifth IEEE World Congress on Computational Intelligence (WCCI'08), pages 3448-3455, Piscataway NJ, 2008. IEEE Press. [ bib ]

N. Beume, T. Hein, B. Naujoks, G. Neugebauer, N. Piatkowski, M. Preuss, R. Stüer, and A. Thom. To Model or Not to Model: Controlling Pac-Man Ghosts Without Incorporating Global Knowledge. In Proc. 2008 Congress on Evolutionary Computation (CEC'08) within Fifth IEEE World Congress on Computational Intelligence (WCCI'08), pages 3464-3471, Piscataway NJ, 2008. IEEE Press. [ bib ]

J. Jägersküpper and M. Preuss. Aiming for a theoretically tractable csa variant by means of empirical investigations. In C. Ryan and M. Keijzer, editors, Genetic and Evolutionary Computation Conference, GECCO 2008, Proceedings, Atlanta, GA, USA, July 12-16, 2008, pages 503-510. ACM, 2008. (GECCO'08 best paper award, evolution strategy track). [ bib ]

J. Jägersküpper and M. Preuss. Empirical investigation of simplified step-size control in metaheuristics with a view to theory. In C. C. McGeoch, editor, Experimental Algorithms, 7th International Workshop, WEA 2008, Proceedings, volume 5038 of Lecture Notes in Computer Science, pages 263-274, Berlin, 2008. Springer. [ bib ]

H. Trautmann, U. Ligges, J. Mehnen, and M. Preuss. A convergence criterion for multiobjective evolutionary algorithms based on systematic statistical testing. In Parallel Problem Solving from Nature - PPSN X, 10th International Conference Dortmund, Germany, September 13-17, 2008, Proceedings, volume 5199 of Lecture Notes in Computer Science, pages 825-836, Berlin, 2008. Springer. [ bib ]

C. Stoean, M. Preuss, R. Stoean, and D. Dumitrescu. Ea-powered basin number estimation by means of preservation and exploration. In G. Rudolph, T. Jansen, S. M. Lucas, C. Poloni, and N. Beume, editors, Parallel Problem Solving from Nature - PPSN X, 10th International Conference Dortmund, Germany, September 13-17, 2008, Proceedings, volume 5199 of Lecture Notes in Computer Science, pages 569-578, Berlin, 2008. Springer. [ bib ]

C. Kausch, M. Preuss, C. Bouvy, and F. Henrich. Multi-criteria pareto optimised planning method for distillation plants with nonsharp splits. In A. Ziebik, Z. Kolenda, and W. Stanek, editors, ECOS 2008, pages 773-780. AGH University of Science & Technology, 2008. [ bib | pdf download  ]

M. Preuss, C. Kausch, C. Bouvy, and F. Henrich. Decision space diversity can be essential for solving multiobjective real-world problems. In M. Ehrgott et al., editors, MCDM for Sustainable Energy and Transportation Systems, EMO Track, page in press, Berlin, 2008. Springer. [ bib ]

C. Bouvy, C. Kausch, M. Preuss, and F. Henrich. On the potential of multi-objective optimisation in the design of sustainable energy systems. In M. Ehrgott et al., editors, MCDM for Sustainable Energy and Transportation Systems, page in press, Berlin, 2008. Springer. [ bib ]

2007:

C. Stoean, R. Stoean, M. Preuss, and D. Dumitrescu. Competitive coevolution for classification. In 7th International Conference on Artificial Intelligence and Digital Communications (AIDC 2007), pages 28-39, Craiova, Romania, 2007. Research Notes in Artificial Intelligence and Digital Communications, N. Tandareanu (Ed.), Reprograph Press. [ bib ]

R. Stoean, C. Stoean, M. Preuss, and D. Dumitrescu. Evolutionary detection of separating hyperplanes in e-mail classification. Acta Cibiniensis, LV:41-46, 2007. [ bib ]

F. Henrich, C. Bouvy, C. Kausch, K. Lucas, M. Preuss, G. Rudolph, and P. Roosen. Economic optimization of non-sharp separation sequences by means of evolutionary algorithms. Computers chem. Engng., 32(7):1411-1432, 2007. [ bib ]

M. Chimani, M. Kandyba, and M. Preuss. Hybrid numerical optimization for combinatorial network problems. In T. Bartz-Beielstein, M. J. B. Aguilera, C. Blum, B. Naujoks, A. Roli, G. Rudolph, and M. Sampels, editors, Hybrid Metaheuristics, 4th International Workshop, HM 2007, Dortmund, Germany, October 8-9, 2007, Proceedings, volume 4771 of Lecture Notes in Computer Science, pages 185-200. Springer, 2007. [ bib | DOI ]

C. Stoean, M. Preuss, R. Stoean, and D. Dumitrescu. Disburdening the species conservation evolutionary algorithm of arguing with radii. In H. Lipson, editor, Genetic and Evolutionary Computation Conference, GECCO 2007, Proceedings, London, England, UK, July 7-11, 2007, pages 1420-1427. ACM, 2007. [ bib | DOI ]

R. Stoean, M. Preuss, C. Stoean, and D. Dumitrescu. Concerning the potential of evolutionary support vector machines. In D. Srinivasan and L. Wang, editors, 2007 IEEE Congress on Evolutionary Computation, pages 1436-1443, Singapore, 2007. IEEE Computational Intelligence Society, IEEE Press. [ bib ]

M. Preuss, G. Rudolph, and F. Tumakaka. Solving multimodal problems via multiobjective technique with application to phase equilibrium detection. In D. Srinivasan and L. Wang, editors, 2007 IEEE Congress on Evolutionary Computation, pages 2703-2710, Singapore, 2007. IEEE Computational Intelligence Society, IEEE Press. [ bib ]

G. Rudolph, B. Naujoks, and M. Preuss. Capabilities of emoa to detect and preserve equivalent pareto subsets. In S. Obayashi, K. Deb, C. Poloni, T. Hiroyasu, and T. Murata, editors, Evolutionary Multi-Criterion Optimization, 4th International Conference, EMO 2007, Matsushima, Japan, March 5-8, 2007, Proceedings, volume 4403 of Lecture Notes in Computer Science, pages 36-50. Springer, 2007. [ bib ]

M. Preuß and T. Bartz-Beielstein. Sequential parameter optimization applied to self-adaptation for binary-coded evolutionary algorithms. In F. Lobo, C. Lima, and Z. Michalewicz, editors, Parameter Setting in Evolutionary Algorithms, Studies in Computational Intelligence, pages 91-120. Springer, Berlin, Heidelberg, New York, 2007. [ bib ]

2006:

R. Stoean, D. Dumitrescu, M. Preuss, and C. Stoean. Different techniques of multi-class evolutionary support vector machines. In L. P. D. Dumitrescu, editor, Bio-Inspired Computing: Theory and Applications (BIC-TA 2006), pages 299-306, China, 2006. [ bib ]

C. Stoean, D. Dumitrescu, M. Preuss, and R. Stoean. Cooperative coevolution for classification. In L. P. D. Dumitrescu, editor, Bio-Inspired Computing: Theory and Applications (BIC-TA 2006), pages 289-298, China, 2006. [ bib ]

C. Stoean, R. Stoean, M. Preuss, and D. Dumitrescu. A cooperative evolutionary algorithm for classification. International Journal of Computers, Communications & Control, (Supplementary Issue, International Conference on Computers and Communications - ICCC 2006, Baile Felix Spa - Oradea, Romania):417-422, 2006. [ bib ]

R. Stoean, C. Stoean, M. Preuss, and D. Dumitrescu. Evolutionary multi-class support vector machines for classification. International Journal of Computers, Communications & Control, (Supplementary Issue, International Conference on Computers and Communications - ICCC 2006, Baile Felix Spa - Oradea, Romania):423-428, 2006. [ bib ]

R. Stoean, C. Stoean, M. Preuss, E. El-Darzi, and D. Dumitrescu. Evolutionary Support Vector Machines for Diabetes Mellitus Diagnosis. In Proceedings 3rd International IEEE Conference on Intelligent Systems - IS 2006, University of Westminster, London, pages 182-187, Piscataway, NJ, 2006. IEEE Press. [ bib ]

R. Stoean, C. Stoean, M. Preuss, and D. Dumitrescu. Evolutionary Support Vector Machines for Spam Filtering. In R. Brad, editor, RoEduNet IEEE International Conference, Sibiu, Romania, pages 261-266, 2006. [ bib ]

C. Stoean, R. Stoean, M. Preuss, and D. Dumitrescu. Spam Filtering by Means of Cooperative Coevolution. In H. N. Teodorescu, editor, 4th European Conference on Intelligent Systems and Technologies, ECIT 2006, Iasi, Romania, pages 157-159. Performantica Press, 2006. [ bib ]

R. Stoean, C. Stoean, M. Preuss, and D. Dumitrescu. Forecasting Soybean Diseases from Symptoms by Means of Evolutionary Support Vector Machines. Phytologia Balcanica, 12(3):345-350, 2006. [ bib ]

M. Preuss. Niching Prospects. In B. Filipic and J. Silc, editors, Bioinspired Optimization Methods and their Applications (BIOMA 2006), pages 25-34. Jozef Stefan Institute, Ljubljana, Slovenia, 2006. [ bib | pdf download  ]

R. Stoean, D. Dumitrescu, M. Preuss, and C. Stoean. Evolutionary Support Vector Regression Machines. In L. O'Conner, editor, 8th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2006), pages 330-335, Los Alamitos, CA, USA, 2006. IEEE Computer Society. [ bib | pdf download  ]

C. Stoean, M. Preuss, D. Dumitrescu, and R. Stoean. Cooperative Evolution of Rules for Classification. In L. O'Conner, editor, 8th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2006), pages 317-322, Los Alamitos, CA, USA, 2006. IEEE Computer Society. [ bib | pdf download  ]

T. Bartz-Beielstein, M. Preuss, and G. Rudolph. Investigation of one-go evolution strategy/quasi-newton hybridizations. In F. A. et al., editor, Hybrid Metaheuristics, Third International Workshop, HM 2006, Proceedings, volume 4030 of Lecture Notes in Computer Science, pages 178-191, Berlin, 2006. Springer. [ bib | pdf download  ]

M. Preuß, B. Naujoks, and G. Rudolph. Pareto set and EMOA behavior for simple multimodal multiobjective functions. In T. P. Runarsson, H.-G. Beyer, E. Burke, J. J. Merelo-Guervós, L. D. Whitley, and X. Yao, editors, Parallel Problem Solving from Nature - PPSN IX, Proc. Ninth Int'l Conf., Reykjavik, volume 4193 of Lecture Notes in Computer Science, pages 513-522, Berlin, 2006. Springer. [ bib | pdf download  ]

M. Giacobini, M. Preuß, and M. Tomassini. Effects of scale-free and small-world topologies on binary coded self-adaptive CEA. In J. Gottlieb and G. R. Raidl, editors, Sixth European Conf. Evolutionary Computation in Combinatorial Optimization, Proc. (EvoCOP'06), volume 3906 of Lecture Notes in Computer Science, pages 86-98, Berlin, 2006. Springer. [ bib | pdf download  ]

T. Bartz-Beielstein and M. Preuss. Considerations of Budget Allocation for Sequential Parameter Optimization (SPO). In L. Paquete, M. Chiarandini, and D. Basso, editors, Empirical Methods for the Analysis of Algorithms, Workshop EMAA 2006, Proceedings, pages 35-40, Reykjavik, Iceland, September 2006. [ bib | pdf download  ]

2005:

C. Stoean, R. Stoean, M. Preuss, and D. Dumitrescu. Diabetes diagnosis through the means of a multimodal evolutionary algorithm. In B. McKay et al., editors, Proc. 1st East European Conference on Health Care Modelling and Computation (HCMC'2005), Craiova, Romania, pages 277-289, Craiova, 2005. Medical University Press. [ bib | pdf download  ]

C. Stoean, M. Preuss, R. Gorunescu, and D. Dumitrescu. Elitist Generational Genetic Chromodynamics - a New Radii-Based Evolutionary Algorithm for Multimodal Optimization. In B. McKay et al., editors, Proc. 2005 Congress on Evolutionary Computation (CEC'05), Edinburgh, Scotland, volume 2, pages 1839-1846, Piscataway NJ, 2005. IEEE Press. [ bib | pdf download  ]

T. Bartz-Beielstein, C. Lasarczyk, and M. Preuß. Sequential parameter optimization. In B. McKay et al., editors, Proc. 2005 Congress on Evolutionary Computation (CEC'05), Edinburgh, Scotland, volume 1, pages 773-780, Piscataway NJ, 2005. IEEE Press. [ bib | pdf download  ]

M. Preuss, L. Schönemann, and M. Emmerich. Counteracting genetic drift and disruptive recombination in (μ +/, λ)-EA on multimodal fitness landscapes. In H.-G. Beyer et al., editors, Proc. Genetic and Evolutionary Computation Conf. (GECCO 2005), Washington D.C., volume 1, pages 865-872, New York, 2005. ACM Press. [ bib | pdf download  ]

T. Bartz-Beielstein, M. Preuss, and S. Markon. Validation and optimization of an elevator simulation model with modern search heuristics. In T. Ibaraki, K. Nonobe, and M. Yagiura, editors, Metaheuristics : Progress as Real Problem Solvers, chapter 5, pages 109-128. Kluwer Academic Publishers, Boston, USA, 2005. [ bib | pdf download  ]

2004:

C. Stoean, R. Gorunescu, M. Preuss, and D. Dumitrescu. An evolutionary learning classifier system applied to text categorization. Annal of West University of Timisoara, Mathematics and Computer Science Series, XLII(special issue 1):265-278, 2004. [ bib ]

L. Schönemann, M. Emmerich, and M. Preuß. On the extinction of evolutionary algorithm subpopulations on multimodal landscapes. Informatica (Slowenien), 28(4):345-351, 2004. [ bib ]

L. Schönemann, M. Emmerich, and M. Preuss. On the extiction of sub-populations on multimodal landscapes. In B. Filipič and J. Šilc, editors, Proc. Int'l Conf. Bioinspired Optimization Methods and their Applications (BIOMA'04), pages 31-40, Ljubljana, Slovenia, 2004. Jožef Stefan Institute. [ bib | pdf download  ]

C. Stoean, R. Gorunescu, M. Preuss, and D. Dumitrescu. An evolutionary learning spam filter system. In D. Petcu, D. Zaharie, V. Negru, and T. Jebelean, editors, Proceedings 6th International Symposium, SYNASC04 - Symbolic and Numeric Algorithms for Scientific Computing, pages 512-522, Timisoara, Romania, 26 - 30 September 2004. Mirton Publishing House. ISBN 973-661-441-7. [ bib | pdf download  ]

C. Stoean, R. Gorunescu, M. Preuss, and D. Dumitrescu. Evolutionary detection of rules for text categorization. application to spam filtering. In H.-N. Teodorescu, editor, Intelligent Systems - Fuzzy Systems, Neural Networks, Genetic Algorithms, Heuristics and Nonlinear Systems - Selected papers of the Third European Conference on Intelligent Systems and Technologies - ECIT'2004, pages 87-95, Iasi, Romania, 21 - 23 July 2004. Performantica Press. [ bib | pdf download  ]

M. Preuss and C. Lasarczyk. On the importance of information speed in structured populations. In X. Yao, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo-Guervós, J. A. Bullinaria, J. Rowe, P. T. A. Kabán, and H.-P. Schwefel, editors, Parallel Problem Solving from Nature - PPSN VIII, volume 3242 of LNCS, pages 90-99, Birmingham, UK, 18-22 Sept. 2004. Springer. [ bib | pdf download  ]

2003:

T. Beielstein, S. Markon, and M. Preuß. Algorithm based validation of a simplified elevator group controller model. In T. Ibaraki, editor, Proc. 5th Metaheuristics Int'l Conf. (MIC'03), pages 06/1-06/13 (CD-ROM), Kyoto, Japan, 2003. [ bib | pdf download  ]

T. Beielstein, S. Markon, and M. Preuß. A parallel approach to elevator optimization based on soft computing. In T. Ibaraki, editor, Proc. 5th Metaheuristics Int'l Conf. (MIC'03), pages 07/1-07/11 (CD-ROM), Kyoto, Japan, 2003. [ bib | pdf download  ]

2002:

M. G. Arenas, P. Collet, A. E. Eiben, M. Jelasity, J. J. Merelo, B. Paechter, M. Preuß, and M. Schoenauer. A framework for distributed evolutionary algorithms. In J. J. M. Guervós, P. Adamidis, H.-G. Beyer, J. L. Fernández-Villacañas, and H.-P. Schwefel, editors, Parallel Problem Solving from Nature - PPSN VII, Proc. Seventh Int'l Conf., Granada, September 2002, volume 2439 of Lecture Notes in Computer Science, pages 665-675, Berlin, 2002. Springer. [ bib | pdf download  ]

M. Jelasity, M. Preuß, and A. E. Eiben. Operator learning for a problem class in a distributed peer-to-peer environment. In J. J. M. Guervós, P. Adamidis, H.-G. Beyer, J. L. Fernández-Villacañas, and H.-P. Schwefel, editors, Parallel Problem Solving from Nature - PPSN VII, Proc. Seventh Int'l Conf., Granada, September 2002, volume 2439 of Lecture Notes in Computer Science, pages 172-183, Berlin, 2002. Springer. [ bib | pdf download  ]

M. Jelasity and M. Preuß. On obtaining global information in a peer-to-peer fully distributed environment. In B. Monien and R. Feldman, editors, Euro-Par 2002 Parallel Processing, Proc. Eighth Int'l Conf., Paderborn, August 2002, volume 2400 of Lecture Notes in Computer Science, pages 573-577, Berlin, 2002. Springer. [ bib | pdf download  ]

M. Jelasity, M. Preuß, M. van Steen, and B. Paechter. Maintaining connectivity in a scalable and robust distributed environment. In H. E. Bal, K.-P. Löhr, and A. Reinefeld, editors, Proc. Second IEEE Int'l Symposium on Cluster Computing and the Grid (CCGrid'02), pages 389-394, Los Alamitos CA, 2002. IEEE Computer Society. [ bib | pdf download  ]

M. Jelasity, M. Preuß, and B. Paechter. A scalable and robust framework for distributed applications. In D. B. Fogel, M. A. El-Sharkawi, X. Yao, G. Greenwood, H. Iba, P. Marrow, and M. Shackleton, editors, Proc. 2002 Congress on Evolutionary Computation (CEC'02) within Third IEEE World Congress on Computational Intelligence (WCCI'02), Honolulu HI, pages 1540-1545, Piscataway NJ, 2002. IEEE Press. [ bib | pdf download  ]

vor 2002:

T. Bäck, A. Eiben, J. de Graaf, M. Preuss, A. Schippers, and H. Taale. Optimizing traffic light controllers with evolutionary algorithms. In Proceedings of the 6th European Congress on Intelligent Techniques and Soft Computing, pages 1730-1734. Verlag Mainz, Aachen, 1998. [ bib ]

weitere Veröffentlichungen, die anders nicht zugänglich sind:

B. Paechter, J. Willies, and M. Preuss. Prologue. In T. Bartz-Beielstein, G. Jankord, B. Naujoks, G. Rudolph, and K. Schmitt, editors, Hans-Paul Schwefel - Festschrift. University of Dortmund, Chair of Systems Analysis, 2006. [ bib | pdf download  ]

T. Bartz-Beielstein and M. Preuss. Moderne methoden zur experimentellen analyse evolutionärer verfahren. In R. Mikut and M. Reischl, editors, Proc. 16th Workshop Computational Intelligence, pages 25-32. Universitätsverlag, Karlsruhe, 2006. in German. [ bib | pdf download  ]

M. Preuss. Reporting on Experiments in Evolutionary Computation. Technical Report CI-221/07, University of Dortmund, SFB 531, 2007. [ bib | pdf download  ]

V. L. Huang, A. K. Qin, K. Deb, E. Zitzler, P. N. Suganthan, J. J. Liang, M. Preuss, and S. Huband. Problem definitions for performance assessment of multi-objective optimization algorithms. Technical report, Nanyang Technological University, Singapore, 2007. [ bib | pdf download  ]

M. Chiarandini, L. Paquete, M. Preuss, and E. Ridge. Experiments on metaheuristics: Methodological overview and open issues. Technical Report DMF-2007-03-003, The Danish Mathematical Society, 2007. [ bib | pdf download  ]

G. Rudolph and M. Preuss. Ein mehrkriterielles evolutionsverfahren zur bestimmung des phasengleichgewichts von gemischten flüssigkeiten. In R. Mikut and M. Reischl, editors, Proc. 17th Workshop Computational Intelligence, pages 177-185. Universitätsverlag, Karlsruhe, 2007. (in German). [ bib ]

M. Preuss and B. Naujoks. Evolutionäre mehrkriterielle optimierung bei anwendungen mit nichtzusammenhängenden pareto-mengen. In R. Mikut and M. Reischl, editors, Proc. 17th Workshop Computational Intelligence, pages 165-176. Universitätsverlag, Karlsruhe, 2007. (in German). [ bib ]

T. Bartz-Beielstein and M. Preuss. Experimental research in evolutionary computation. In D. Thierens, editor, Genetic and Evolutionary Computation Conference, GECCO 2007, Proceedings, London, England, UK, July 7-11, 2007, Companion Material, pages 3001-3020. ACM, 2007. [ bib | DOI ]

T. Bartz-Beielstein and M. Preuss. Experimental research in evolutionary computation. In C. Ryan and M. Keijzer, editors, Genetic and Evolutionary Computation Conference, GECCO 2008, Proceedings, Atlanta, GA, USA, July 12-16, 2008, Companion Material, pages 2517-2534. ACM, 2008. [ bib | DOI ]

G. Rudolph and M. Preuss. Ein evolutionsverfahren zur approximation äquivalenter urbilder von pareto-optimalen zielvektoren. In R. Mikut and M. Reischl, editors, Proc. 18th GMA Workshop Computational Intelligence, pages 30-39. Universitätsverlag, Karlsruhe, 2008. (in German). [ bib ]

G. Rudolph, M. Preuss, and J. Quadflieg. Double-layered surrogate modeling for tuning metaheuristics. In ENBIS/EMSE Conference Design and Analysis of Computer Experiments, Saint-Etienne (France), July 1-3, 2009. [ bib ]