---
res:
  bibo_abstract:
  - '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.@eng'
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: L
      foaf_name: Li, L
      foaf_surname: Li
  - foaf_Person:
      foaf_givenName: Y
      foaf_name: Wang, Y
      foaf_surname: Wang
  - foaf_Person:
      foaf_givenName: Heike
      foaf_name: Trautmann, Heike
      foaf_surname: Trautmann
      foaf_workInfoHomepage: http://www.librecat.org/personId=100740
    orcid: 0000-0002-9788-8282
  - foaf_Person:
      foaf_givenName: N
      foaf_name: Jing, N
      foaf_surname: Jing
  - foaf_Person:
      foaf_givenName: M
      foaf_name: Emmerich, M
      foaf_surname: Emmerich
  bibo_doi: 10.1016/j.swevo.2018.02.006
  bibo_volume: 40
  dct_date: 2018^xs_gYear
  dct_language: eng
  dct_title: Multiobjective evolutionary algorithms based on target region preferences@
...