---
_id: '46353'
abstract:
- lang: eng
  text: 'Incorporating decision makers'' preferences is of great significance in multiobjective
    optimization. Target region-based multiobjective evolutionary algorithms (TMOEAs),
    aiming at a well-distributed subset of Pareto optimal solutions within the user-provided
    region(s), are extensively investigated in this paper. An empirical comparison
    is performed among three TMOEA instantiations: T-NSGA-II, T-SMS-EMOA and T-R2-EMOA.
    Experimental results show that T-SMS-EMOA has the best overall performance regarding
    the hypervolume indicator within the target region, while T-NSGA-II is the fastest
    algorithm. We also compare TMOEAs with other state-of-the-art preference-based
    approaches, i.e., DF-SMS-EMOA, RVEA, AS-EMOA and R-NSGA-II to show the advantages
    of TMOEAs. A case study in the mission planning of earth observation satellite
    is carried out to verify the capabilities of TMOEAs in the real-world application.
    Experimental results indicate that preferences can improve the searching ability
    of MOEAs, and TMOEAs can successfully find nondominated solutions preferred by
    the decision maker.'
author:
- first_name: L
  full_name: Li, L
  last_name: Li
- first_name: Y
  full_name: Wang, Y
  last_name: Wang
- first_name: Heike
  full_name: Trautmann, Heike
  id: '100740'
  last_name: Trautmann
  orcid: 0000-0002-9788-8282
- first_name: N
  full_name: Jing, N
  last_name: Jing
- first_name: M
  full_name: Emmerich, M
  last_name: Emmerich
citation:
  ama: Li L, Wang Y, Trautmann H, Jing N, Emmerich M. Multiobjective evolutionary
    algorithms based on target region preferences. <i>Swarm and Evolutionary Computation</i>.
    2018;40:196–215. doi:<a href="https://doi.org/10.1016/j.swevo.2018.02.006">10.1016/j.swevo.2018.02.006</a>
  apa: Li, L., Wang, Y., Trautmann, H., Jing, N., &#38; Emmerich, M. (2018). Multiobjective
    evolutionary algorithms based on target region preferences. <i>Swarm and Evolutionary
    Computation</i>, <i>40</i>, 196–215. <a href="https://doi.org/10.1016/j.swevo.2018.02.006">https://doi.org/10.1016/j.swevo.2018.02.006</a>
  bibtex: '@article{Li_Wang_Trautmann_Jing_Emmerich_2018, title={Multiobjective evolutionary
    algorithms based on target region preferences}, volume={40}, DOI={<a href="https://doi.org/10.1016/j.swevo.2018.02.006">10.1016/j.swevo.2018.02.006</a>},
    journal={Swarm and Evolutionary Computation}, author={Li, L and Wang, Y and Trautmann,
    Heike and Jing, N and Emmerich, M}, year={2018}, pages={196–215} }'
  chicago: 'Li, L, Y Wang, Heike Trautmann, N Jing, and M Emmerich. “Multiobjective
    Evolutionary Algorithms Based on Target Region Preferences.” <i>Swarm and Evolutionary
    Computation</i> 40 (2018): 196–215. <a href="https://doi.org/10.1016/j.swevo.2018.02.006">https://doi.org/10.1016/j.swevo.2018.02.006</a>.'
  ieee: 'L. Li, Y. Wang, H. Trautmann, N. Jing, and M. Emmerich, “Multiobjective evolutionary
    algorithms based on target region preferences,” <i>Swarm and Evolutionary Computation</i>,
    vol. 40, pp. 196–215, 2018, doi: <a href="https://doi.org/10.1016/j.swevo.2018.02.006">10.1016/j.swevo.2018.02.006</a>.'
  mla: Li, L., et al. “Multiobjective Evolutionary Algorithms Based on Target Region
    Preferences.” <i>Swarm and Evolutionary Computation</i>, vol. 40, 2018, pp. 196–215,
    doi:<a href="https://doi.org/10.1016/j.swevo.2018.02.006">10.1016/j.swevo.2018.02.006</a>.
  short: L. Li, Y. Wang, H. Trautmann, N. Jing, M. Emmerich, Swarm and Evolutionary
    Computation 40 (2018) 196–215.
date_created: 2023-08-04T07:56:57Z
date_updated: 2023-10-16T13:34:21Z
department:
- _id: '34'
- _id: '819'
doi: 10.1016/j.swevo.2018.02.006
intvolume: '        40'
language:
- iso: eng
page: 196–215
publication: Swarm and Evolutionary Computation
status: public
title: Multiobjective evolutionary algorithms based on target region preferences
type: journal_article
user_id: '15504'
volume: 40
year: '2018'
...