my publications (only the peer reviewed ones)
in reverse chronological order:
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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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prior to 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 ]
further publications which are not available otherwise:
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 |
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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 ]