---
_id: '46408'
abstract:
- lang: eng
  text: The integration of experts’ preferences is an important aspect in multi-objective
    optimization. Usually, one out of a set of Pareto optimal solutions has to be
    chosen based on expert knowledge. A combination of multi-objective particle swarm
    optimization (MOPSO) with the desirability concept is introduced to efficiently
    focus on desired and relevant regions of the true Pareto front of the optimization
    problem which facilitates the solution selection process. Desirability functions
    of the objectives are optimized, and the desirability index is used for selecting
    the global best particle in each iteration. The resulting MOPSO variant DF-MOPSO
    in most cases exclusively generates solutions in the desired area of the Pareto
    front. Approximations of the whole Pareto front result in cases of misspecified
    desired regions.
author:
- first_name: Sanaz
  full_name: Mostaghim, Sanaz
  last_name: Mostaghim
- first_name: Heike
  full_name: Trautmann, Heike
  id: '100740'
  last_name: Trautmann
  orcid: 0000-0002-9788-8282
- first_name: Olaf
  full_name: Mersmann, Olaf
  last_name: Mersmann
citation:
  ama: 'Mostaghim S, Trautmann H, Mersmann O. Preference-Based Multi-Objective Particle
    Swarm Optimization Using Desirabilities. In: Schaefer R, Cotta C, Kołodziej J,
    Rudolph G, eds. <i>Parallel Problem Solving from Nature, PPSN XI</i>. Springer
    Berlin Heidelberg; 2010:101–110. doi:<a href="https://doi.org/10.1007/978-3-642-15871-1_11">https://doi.org/10.1007/978-3-642-15871-1_11</a>'
  apa: Mostaghim, S., Trautmann, H., &#38; Mersmann, O. (2010). Preference-Based Multi-Objective
    Particle Swarm Optimization Using Desirabilities. In R. Schaefer, C. Cotta, J.
    Kołodziej, &#38; G. Rudolph (Eds.), <i>Parallel Problem Solving from Nature, PPSN
    XI</i> (pp. 101–110). Springer Berlin Heidelberg. <a href="https://doi.org/10.1007/978-3-642-15871-1_11">https://doi.org/10.1007/978-3-642-15871-1_11</a>
  bibtex: '@inproceedings{Mostaghim_Trautmann_Mersmann_2010, place={Berlin, Heidelberg},
    title={Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities},
    DOI={<a href="https://doi.org/10.1007/978-3-642-15871-1_11">https://doi.org/10.1007/978-3-642-15871-1_11</a>},
    booktitle={Parallel Problem Solving from Nature, PPSN XI}, publisher={Springer
    Berlin Heidelberg}, author={Mostaghim, Sanaz and Trautmann, Heike and Mersmann,
    Olaf}, editor={Schaefer, Robert and Cotta, Carlos and Kołodziej, Joanna and Rudolph,
    Günter}, year={2010}, pages={101–110} }'
  chicago: 'Mostaghim, Sanaz, Heike Trautmann, and Olaf Mersmann. “Preference-Based
    Multi-Objective Particle Swarm Optimization Using Desirabilities.” In <i>Parallel
    Problem Solving from Nature, PPSN XI</i>, edited by Robert Schaefer, Carlos Cotta,
    Joanna Kołodziej, and Günter Rudolph, 101–110. Berlin, Heidelberg: Springer Berlin
    Heidelberg, 2010. <a href="https://doi.org/10.1007/978-3-642-15871-1_11">https://doi.org/10.1007/978-3-642-15871-1_11</a>.'
  ieee: 'S. Mostaghim, H. Trautmann, and O. Mersmann, “Preference-Based Multi-Objective
    Particle Swarm Optimization Using Desirabilities,” in <i>Parallel Problem Solving
    from Nature, PPSN XI</i>, 2010, pp. 101–110, doi: <a href="https://doi.org/10.1007/978-3-642-15871-1_11">https://doi.org/10.1007/978-3-642-15871-1_11</a>.'
  mla: Mostaghim, Sanaz, et al. “Preference-Based Multi-Objective Particle Swarm Optimization
    Using Desirabilities.” <i>Parallel Problem Solving from Nature, PPSN XI</i>, edited
    by Robert Schaefer et al., Springer Berlin Heidelberg, 2010, pp. 101–110, doi:<a
    href="https://doi.org/10.1007/978-3-642-15871-1_11">https://doi.org/10.1007/978-3-642-15871-1_11</a>.
  short: 'S. Mostaghim, H. Trautmann, O. Mersmann, in: R. Schaefer, C. Cotta, J. Kołodziej,
    G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI, Springer Berlin
    Heidelberg, Berlin, Heidelberg, 2010, pp. 101–110.'
date_created: 2023-08-04T16:06:43Z
date_updated: 2023-10-16T13:56:31Z
department:
- _id: '34'
- _id: '819'
doi: https://doi.org/10.1007/978-3-642-15871-1_11
editor:
- first_name: Robert
  full_name: Schaefer, Robert
  last_name: Schaefer
- first_name: Carlos
  full_name: Cotta, Carlos
  last_name: Cotta
- first_name: Joanna
  full_name: Kołodziej, Joanna
  last_name: Kołodziej
- first_name: Günter
  full_name: Rudolph, Günter
  last_name: Rudolph
language:
- iso: eng
page: 101–110
place: Berlin, Heidelberg
publication: Parallel Problem Solving from Nature, PPSN XI
publication_identifier:
  isbn:
  - 978-3-642-15871-1
publisher: Springer Berlin Heidelberg
status: public
title: Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities
type: conference
user_id: '15504'
year: '2010'
...
---
_id: '46409'
abstract:
- lang: eng
  text: Since many real-world optimization problems are noisy, vector optimization
    algorithms that can cope with noise and uncertainty are required. We propose new,
    robust selection strategies for evolutionary multi-objective optimization in the
    presence of noise. We apply new measures of uncertainty for estimating the recently
    introduced Pareto-dominance for uncertain and noisy environments (PDU). The first
    measure is the inter-quartile range of the outcomes of repeated function evaluations.
    The second is based on axis-aligned bounding boxes around the upper and lower
    quantiles of the sampled fitness values in objective space. Experiments on real
    and artificial problems show promising results.
author:
- first_name: Thomas
  full_name: Voß, Thomas
  last_name: Voß
- first_name: Heike
  full_name: Trautmann, Heike
  id: '100740'
  last_name: Trautmann
  orcid: 0000-0002-9788-8282
- first_name: Christian
  full_name: Igel, Christian
  last_name: Igel
citation:
  ama: 'Voß T, Trautmann H, Igel C. New Uncertainty Handling Strategies in Multi-objective
    Evolutionary Optimization. In: Schaefer R, Cotta C, Kołodziej J, Rudolph G, eds.
    <i>Parallel Problem Solving from Nature, PPSN XI</i>. Springer Berlin Heidelberg;
    2010:260–269. doi:<a href="https://doi.org/10.1007/978-3-642-15871-1_27">https://doi.org/10.1007/978-3-642-15871-1_27</a>'
  apa: Voß, T., Trautmann, H., &#38; Igel, C. (2010). New Uncertainty Handling Strategies
    in Multi-objective Evolutionary Optimization. In R. Schaefer, C. Cotta, J. Kołodziej,
    &#38; G. Rudolph (Eds.), <i>Parallel Problem Solving from Nature, PPSN XI</i>
    (pp. 260–269). Springer Berlin Heidelberg. <a href="https://doi.org/10.1007/978-3-642-15871-1_27">https://doi.org/10.1007/978-3-642-15871-1_27</a>
  bibtex: '@inproceedings{Voß_Trautmann_Igel_2010, place={Berlin, Heidelberg}, title={New
    Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization},
    DOI={<a href="https://doi.org/10.1007/978-3-642-15871-1_27">https://doi.org/10.1007/978-3-642-15871-1_27</a>},
    booktitle={Parallel Problem Solving from Nature, PPSN XI}, publisher={Springer
    Berlin Heidelberg}, author={Voß, Thomas and Trautmann, Heike and Igel, Christian},
    editor={Schaefer, Robert and Cotta, Carlos and Kołodziej, Joanna and Rudolph,
    Günter}, year={2010}, pages={260–269} }'
  chicago: 'Voß, Thomas, Heike Trautmann, and Christian Igel. “New Uncertainty Handling
    Strategies in Multi-Objective Evolutionary Optimization.” In <i>Parallel Problem
    Solving from Nature, PPSN XI</i>, edited by Robert Schaefer, Carlos Cotta, Joanna
    Kołodziej, and Günter Rudolph, 260–269. Berlin, Heidelberg: Springer Berlin Heidelberg,
    2010. <a href="https://doi.org/10.1007/978-3-642-15871-1_27">https://doi.org/10.1007/978-3-642-15871-1_27</a>.'
  ieee: 'T. Voß, H. Trautmann, and C. Igel, “New Uncertainty Handling Strategies in
    Multi-objective Evolutionary Optimization,” in <i>Parallel Problem Solving from
    Nature, PPSN XI</i>, 2010, pp. 260–269, doi: <a href="https://doi.org/10.1007/978-3-642-15871-1_27">https://doi.org/10.1007/978-3-642-15871-1_27</a>.'
  mla: Voß, Thomas, et al. “New Uncertainty Handling Strategies in Multi-Objective
    Evolutionary Optimization.” <i>Parallel Problem Solving from Nature, PPSN XI</i>,
    edited by Robert Schaefer et al., Springer Berlin Heidelberg, 2010, pp. 260–269,
    doi:<a href="https://doi.org/10.1007/978-3-642-15871-1_27">https://doi.org/10.1007/978-3-642-15871-1_27</a>.
  short: 'T. Voß, H. Trautmann, C. Igel, in: R. Schaefer, C. Cotta, J. Kołodziej,
    G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI, Springer Berlin
    Heidelberg, Berlin, Heidelberg, 2010, pp. 260–269.'
date_created: 2023-08-04T16:07:48Z
date_updated: 2023-10-16T13:56:48Z
department:
- _id: '34'
- _id: '819'
doi: https://doi.org/10.1007/978-3-642-15871-1_27
editor:
- first_name: Robert
  full_name: Schaefer, Robert
  last_name: Schaefer
- first_name: Carlos
  full_name: Cotta, Carlos
  last_name: Cotta
- first_name: Joanna
  full_name: Kołodziej, Joanna
  last_name: Kołodziej
- first_name: Günter
  full_name: Rudolph, Günter
  last_name: Rudolph
language:
- iso: eng
page: 260–269
place: Berlin, Heidelberg
publication: Parallel Problem Solving from Nature, PPSN XI
publication_identifier:
  isbn:
  - 978-3-642-15871-1
publisher: Springer Berlin Heidelberg
status: public
title: New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization
type: conference
user_id: '15504'
year: '2010'
...