Florian Siegmund

Florian Siegmund

Doktorand

Institutionen för ingenjörsvetenskap

Kontaktuppgifter

  • Rum
  • PA210A

I am pursuing a doctoral degree in industrial informatics. My research interest are nature-inspired, heuristic optimization algorithms for simulation-based optimization and decision support, and their strategies to handle uncertainty in the simulation models.

Teaching

Supervised student theses
My teaching page

Journal articles

  • Amos H.C. Ng, Florian Siegmund, and Kalyanmoy Deb. "Dynamic Resampling for Preference-based Industrial System Simulation and Optimization" In preparation for submission to International Journal of Production Economics.
  • Florian Siegmund, Amos H.C. Ng, and Kalyanmoy Deb. "Standard Error Dynamic Resampling for Preference-based Evolutionary Multi-objective Optimization". Submitted to Computers & Operations Research. COIN Report No. 2015021.
  • Florian Siegmund, Amos H.C. Ng, and Kalyanmoy Deb. "Dynamic Resampling for Preference-based Evolutionary Multi-objective Optimization of Stochastic Systems". Submitted to European Journal of Operations Research. COIN Report No. 2015020.

Conference papers

  • Florian Siegmund, Amos H.C. Ng, and Kalyanmoy Deb, 2016. "A Comparative Study of Fast Adaptive Preference-Guided Evolutionary Multi-objective Optimization". Submitted to 14th International Conference on Parallel Problem Solving from Nature, September 2016, Edinburgh, Scotland.
  • Florian Siegmund, Amos H.C. Ng, and Kalyanmoy Deb, 2016. "A Ranking and Selection Strategy for Preference-based Evolutionary Multi-objective Optimization of Variable-Noise Problems". Accepted for publication in the Proceedings of the Congress on Evolutionary Computation WCCI-CEC 2016, July 2016, Vancouver, Canada. COIN Report No. 2016002.
  • Florian Siegmund, Amos H.C. Ng, and Kalyanmoy Deb, 2016. "Hybrid Dynamic Resampling Algorithms for Evolutionary Multi-objective Optimization of Invariant-Noise Problems". In Proceedings of the Evostar-EvoApplications 2016 conference, March 2016, Porto, Portugal, pp. 311-326, ISBN 978-3-319-31152-4. DOI: 10.1007/978-3-319-31153-1_21.
  • Florian Siegmund, Amos H.C. Ng, and Kalyanmoy Deb, 2015. "Hybrid Dynamic Resampling for Guided Evolutionary Multi-Objective Optimization". In Proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, March 2015, Guimarães, Portugal, pp. 366-380, ISBN 978-3-319-15934-8. DOI: 10.1007/978-3-319-15934-8.
  • Kalyanmoy Deb, Florian Siegmund, and Amos H.C. Ng, 2014. "R-HV: A Metric for Computing Hyper-volume for Reference Point-based EMOs". In Proceedings of the International Conference on Swarm, Evolutionary, and Memetic Computing, December 2014, Bhubaneswar, Odisha, India, pp. 98-110, ISBN 978-3-319-20293-8. DOI: 10.1007/978-3-319-20294-5_9.
  • Florian Siegmund, Amos H.C. Ng, and Kalyanmoy Deb, 2013. "A Comparative Study of Dynamic Resampling Strategies for Guided Evolutionary Multi-Objective Optimization". In Proceedings of 2013 IEEE Congress on Evolutionary Computation, June 2013, Cancún, Mexico, pp. 1826-1835, ISBN 978-1-4799-0454-9. DOI: 10.1109/CEC.2013.6557782.
  • Florian Siegmund, Jacob Bernedixen, Leif Pehrsson, Amos H.C. Ng, and Kalyanmoy Deb, 2012. "Reference Point-based Evolutionary Multi-objective Optimization for Industrial Systems Simulation", In Proceedings of Winter Simulation Conference 2012, Dec 2012, Berlin, Germany, ISBN 978-1-4673-4781-5. DOI: 10.1109/WSC.2012.6465130.
  • Florian Siegmund, Amos H.C. Ng, and Kalyanmoy Deb, 2012. "Finding a preferred diverse set of Pareto-optimal solutions for a limited number of function calls", In Proceedings of 2012 IEEE World Congress on Computational Intelligence - Congress on Evolutionary Computation, June 2012, Brisbane, Australia, pp. 2417-2424, ISBN 978-1-4673-1508-1. DOI: 10.1109/CEC.2012.6256654.

Theses

  • Florian Siegmund, 2016. "Dynamic Resampling for Preference-based Evolutionary Multi-objective Optimization of Stochastic Systems", PhD thesis at University of Skövde, Sweden, Sept 2016.
  • Florian Siegmund, 2010. "Optimal Computing Budget Allocation for Noisy Hypervolume-Based Multi-Objective Evolutionary Optimization", Master thesis at Karlsruhe Institute of Technology, Germany and National University of Singapore, Nov 2010.
  • Florian Siegmund, 2009. "Sequential Sampling in Noisy Multi-Objective Evolutionary Optimization", Master thesis at University of Skövde, Sweden and Karlsruhe Institute of Technology, Germany, Sept 2009. [Download]

Talks

  • Florian Siegmund, Amos H.C. Ng, and Kalyanmoy Deb, 2015. "Dynamic Resampling for Preference-based Evolutionary Multi-Objective Optimization of Stochastic Systems", International Conference on Multiple Criteria Decision Making 2015, August 2015, Hamburg, Germany.
  • Florian Siegmund, Amos H.C. Ng, and Kalyanmoy Deb, 2013. "Adaptive Guided Evolutionary Multi-Objective Optimization", International Conference on Multiple Criteria Decision Making 2013, June 2013, Málaga, Spain.
  • Florian Siegmund, Amos H.C. Ng, Alexander Karlsson, and Kalyanmoy Deb, 2013. "Dynamic Resampling for Guided Evolutionary Multi-Objective Optimization of Stochastic Systems", International Conference on Multiple Criteria Decision Making 2013, June 2013, Málaga, Spain.

ResearcherID: F-6692-2010 ,  ORCID: 0000-0003-3432-5068

Publikationer

Florian Siegmund