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Multikriterielle Optimierung

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Multikriterielle Optimierung


Beteiligte Personen
M.Sc. Marlon Braun
Dipl.-Inform. Michael Cipold
Dr.-Ing. Ingo Mauser
Dipl.-Wi.-Ing. Friederike Pfeiffer
PD Dr. rer. nat. Pradyumn Kumar Shukla



Veröffentlichungen zum Forschungsgebiet

Article
Marlon Braun, Sandra Seijo, Javier Echanobe, Pradyumn Kumar Shukla, Indes del Campo, Javier Garcia-Sedano, Hartmut Schmeck
A neuro-genetic approach for modeling and optimizing a complex cogeneration process
Applied Soft Computing, 48, Seiten 347 - 358, August, 2016
(Details)

Pradyumn Kumar Shukla, Marlon Braun, Hartmut Schmeck
A Theoretical and Algorithmic Characterization of Bulge Knees
Optimization Online, Juni, 2015
(Details)

Jan Hettenhausen, Andrew Lewis, Sanaz Mostaghim
Interactive Multi-Objective Particle Swarm Optimisation with Heatmap Visualisation based User Interface.
Journal of Engineering Optimization, 42, (2), Seiten 119-139, Februar, 2010
(Details)

Andreas Fischer, Pradyumn Kumar Shukla, M. Wang
On the inexactness level of robust Levenberg-Marquardt methods
Optimization, 59, (2), Seiten 273 - 287, Februar, 2010
(Details)

Oliver Schütze, Carlos Coello Coello, Sanaz Mostaghim, El-Ghazali Talbi, Michael Dellnitz
Hybridizing Evolutionary Strategies with Continuation Methods for Solving Multi-Objective Problems
Journal of Engineering Optimization, 40, (5), Seiten 383-402, Mai, 2008
(Details)

Jürgen Branke, Thomas Kaußler, Hartmut Schmeck
Guidance in evolutionary multi-objective optimization
Advances in Engineering Software, 32, Seiten 499-507, 2001
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inproceedings
Marlon Braun, Pradyumn Kumar Shukla, Hartmut Schmeck
Obtaining Optimal Pareto Front Approximations using Scalarized Preference Information
Proceedings of the 2015 on Genetic and Evolutionary Computation Conference, Seiten: 631-638, ACM, GECCO '15, New York, Juli, 2015
(Details)

Pradyumn Kumar Shukla, Marlon Braun, Hartmut Schmeck
On the Interrelationships Between Knees and Aggregate Objective Functions
Proceedings of the 2014 Conference Companion on Genetic and Evolutionary Computation Companion, Seiten: 95-96, ACM, GECCO Comp '14, New York, NY, USA
(Details)

Michael Emmerich, Andre deutz, Johannes Kruisselbrink, Pradyumn Kumar Shukla
Cone-based Hypervolume Indicators: Construction, Properties, and Efficient Computation
in EMO 2013, Springer, LNCS
(Details)

Pradyumn Kumar Shukla, Marlon Braun
Indicator Based Search in Variable Orderings: Theory and Algorithms
In Purshouse, Robin C. and Fleming, Peter J. and Fonseca, Carlos M. and Greco, Salvatore and Shaw, Jane, Evolutionary Multi-Criterion Optimization, Seiten: 66-80, Springer Berlin Heidelberg, Lecture Notes in Computer Science, 7811
(Details)

Britto André, Sanaz Mostaghim, Aurora Pozo
Iterated Multi-Swarm
Genetic and Evolutionary Computation Conference (GECCO 2013), ACM, Amsterdam, Juli, 2013
(Details)

Pradyumn Kumar Shukla, Marlon Braun, Hartmut Schmeck
Theory and Algorithms for Finding Knees
In Purshouse, Robin C. and Fleming, Peter J. and Fonseca, Carlos M. and Greco, Salvatore and Shaw, Jane, Evolutionary Multi-Criterion Optimization, Seiten: 156-170, Springer Berlin Heidelberg, Lecture Notes in Computer Science, 7811
(Details)

Pradyumn Kumar Shukla, Michael Emmerich, Andre Deutz
A Theoretical Analysis of Curvature Based Preference Models
in EMO 2013, Springer, LNCS
(Details)

Pradyumn Kumar Shukla, Christian Hirsch, Hartmut Schmeck
Towards a Deeper Understanding of Trade-offs Using Multi-objective Evolutionary Algorithms
EVoStar 2012, Bio-inspired algorithms for continuous parameter optimisation, Seiten: 396--405, Springer, LNCS
(Details)

Michael Cipold, Pradyumn Kumar Shukla, Claus Bachmann, Kaibin Bao, Hartmut Schmeck
An Evolutionary Optimization Approach for Bulk Material Blending Systems
Parallel Problem Solving from Nature - PPSN XII, Springer, Lecture Notes in Computer Science, September, 2012
(Details)

Sanaz Mostaghim, Friederike Pfeiffer, Hartmut Schmeck
Self-organized Invasive Parallel Optimization
Proceedings of the International Workshop on Bio-inspired Approaches for Distributed Computing (BADS), Seiten: 49-56, ACM, Karlsruhe, Juni, 2011
(Details)

Christian Hirsch, Pradyumn Kumar Shukla, Hartmut Schmeck
Variable Preference Modeling using Multi-objective Evolutionary Algorithms
In R. H. C. Takahashi, K. Deb, E. F. Wanner, S. Greco, Evolutionary Multi-Criterion Optimization, Seiten: 91-105, Springer, LNCS, 6576, Berlin / Heidelberg
(Details)

Marlon Braun, Pradyumn Kumar Shukla, Hartmut Schmeck
Preference Ranking Schemes in Multi-objective Evolutionary Algorithms
In Takahashi, Ricardo H.C. and Deb, Kalyanmoy and Wanner, Elizabeth F. and Greco, Salvatore, Evolutionary Multi-Criterion Optimization, Seiten: 226-240, Springer Berlin Heidelberg, Lecture Notes in Computer Science, 6576
(Details)

Sanaz Mostaghim, Heike Trautmann, Olaf Mersmann
Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities
Parallel Problem Solving from Nature (PPSN), Seiten: 101-110, Springer, Berlin Heidelberg, September, 2010
(Details)

Nikhil Padhye, Jürgen Branke, Sanaz Mostaghim
Empirical Comparison of MOPSO methods
Proceedings of the Congress on Evolutionary Computation (CEC'09), Seiten: 2516-2523, IEEE, Trondheim, Norway, Mai, 2009
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Markus Kress, Sanaz Mostaghim, Hartmut Schmeck, Detlef Seese
Gap Search in Particle Swarm Optimization
In https://lsiit.u-strasbg.fr/ea09/index.php/Download, 9th International Conference on Artificial Evolution, EA'09, Oktober, 2009
(Details)

Ian Scriven, Andrew Lewis, Sanaz Mostaghim
Dynamic Search Initialisation Strategies for Multi-Objective Optimisation in Peer-to-Peer Networks
Proceedings of the Congress on Evolutionary Computation (CEC'09), Seiten: 1515-1522, IEEE, Trondheim, Norway, Mai, 2009
(Details)

Sanaz Mostaghim, Hartmut Schmeck
Distance Based Ranking in Many-Objective Particle Swarm Optimization
In G. Rudolph, T. Jansen, S. Lucas, C. Poloni and N. Beume, Parallel Problem Solving from Nature (PPSN), Seiten: 753-762, Springer-Verlag, LNCS 5199, September, 2008
(Details)

Sanaz Mostaghim, Jürgen Branke, Andrew Lewis, Hartmut Schmeck
Parallel multi-objective optimization using a master-slave model on heterogeneous resources
IEEE, Seiten: 1981-1987, Congress on Evolutionary Computation, Juni, 2008
(Details)

Sanaz Mostaghim
High Performance Multi-Objective Optimization
International Conference on Soft Computing and Intelligent Systems, Seiten: 1501-1511, Nagoya, Japan, September, 2008
(Details)

Jürgen Branke, Jochen Gamer
Efficient sampling in interactive multi-criteria selection
Proceedings of the 2007 INFORMS Simulation Society Research Workshop, Seiten: 42-46, INFORMS Simulation Society
(Details)

Sanaz Mostaghim, Jürgen Branke, Hartmut Schmeck
Multi-Objective Particle Swarm Optimization on Computer Grids
In D. Thierens et al., Proceedings of the 2007 Genetic and Evolutionary Computation Conference, Seiten: 869-874, ACM
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Ingo Österreicher, Andreas Mitschele, Frank Schlottmann, Detlef Seese
Comparison of Multi-Objective Evolutionary Algorithms in Optimizing Combinations of Reinsurance Contracts
In Maarten Keijzer et al., GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation, Seiten: 747-748, ACM Press, 1, New York, NY, USA, Juni, 2006
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Jürgen Branke, Kalyanmoy Deb, Henning Dierolf, M. Osswald
Finding knees in multi-objective optimization
Parallel Problem Solving from Nature, Seiten: 722-731, Springer, LNCS, 3242, Dezember, 2004
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book
Andrew Lewis, Sanaz Mostaghim, Marcus Randall
Biologically-inspired Optimisation Methods: Parallel Algorithms, Systems and Applications
Springer, Studies in Computational Intelligence 210, Juni, 2009
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Jürgen Branke
Nature-inspired Design and Optimization of Complex Systems
Postdoctoral thesis, 2006/02/14, Universität Karlsruhe, Februar, 2006
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incollection
Sanaz Mostaghim
Parallel Multi-Objective Optimization using Self-Organized Heterogeneous Resources
In Erick Cantu Paz and Francisco Fernández de Vega, Parallel and Distributed Computational Intelligence, Seiten 165-179, Springer-Verlag, Studies in Computational Intelligence, Berlin Heidelberg, Januar, 2010
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Andreas Mitschele, Frank Schlottmann, Detlef Seese
Integrated Risk Management: Risk Aggregation and Allocation using Intelligent Systems
In E. Kontoghiorghes, B. Rustem, P. Winker, Computational Methods in Financial Engineering, Seiten 317-342, Springer, 2008
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El-Ghazali Talbi, Sanaz Mostaghim, Tatsuya Okabe, Hisao Ishibuchi, Günter Rudolph, Carlos Coello Coello
Parallel Approaches for Multi-Objective Optimization
In J. Branke, K. deb, K. Miettinen and R. Slowinski, MultiObjective Optimization: Interactive and Evolutionary Approaches, Seiten 329--348, Springer-Verlag, LNCS 5252, Berlin Heidelberg, 2008
(Details)

Andrew Lewis, Sanaz Mostaghim, Marcus Randal
Evolutionary Population Dynamics and Multi-Objective Optimisation Problems
In Lam Bui and Sameer Alam, Multi-Objective Optimization in Computational Intelligence: Theory and Practice, Idea Group Publishing, 2008
(Details)

Jürgen Branke, Kalyan Deb
Integrating user preferences into evolutionary multi-objective optimization
In Yaochu Jin, Knowledge Incorporation in Evolutionary Computation, Seiten 461-478, Springer, Oktober, 2004
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Frank Schlottmann, Detlef Seese
Finding constrained downside risk-return efficient credit portfolio structures using hybrid multi-objective evolutionary computation
In G. Bol; G. Nakhaeizadeh; S. Rachev; T. Ridder; K.-H. Vollmer, Credit risk: measurement, evaluation and management, Seiten 231-266, Physica, Heidelberg, 2003
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proceedings
Jürgen Branke, Kalyan Deb, Kaisa Miettinen, Ralph Steuer
Dagstuhl Workshop on Practical Approaches to Multi-Objective Optimization
November, 2005
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techreport
Jürgen Branke, Benedikt Scheckenbach, Michael Stein, Kalyan Deb, Hartmut Schmeck
Portfolio Optimization with an Envelope-based Multi-objective Evolutionary Algorithm
University of Karlsruhe, Institute AIFB, Archiv Nummer 1483 76128 Karlsruhe, Germany, (503), August, 2007
(Details)

Sanaz Mostaghim, Jürgen Branke, Hartmut Schmeck
Multi-Objective Particle Swarm Optimization on Computer Grids
Institute AIFB University of Karlsruhe, Archiv Nummer 1393, (502), Technical Report, Dezember, 2006
(Details)

Jürgen Branke, Thomas Kaußler, Hartmut Schmeck
Guiding Multi Objective Evolutionary Algorithms Towards Interesting Regions
University of Karlsruhe, Institute AIFB, Archiv Nummer 239 76128 Karlsruhe, Germany, (398), Januar, 2000
(Details)

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misc
Ingo Paenke
Efficient Search for Robust Solutions by Means of Evolutionary Algorithms and Fitness Approximation
Diploma (master) thesis , Institute AIFB, University of Karlsruhe, Mai, 2004
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