Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. A Fast Multi-Objective Evolutionary Algorithm applied to Industrial Problems
 
conference paper

A Fast Multi-Objective Evolutionary Algorithm applied to Industrial Problems

Leyland, Geoffrey Basil
•
Favrat, Daniel  
•
Molyneaux, Adam
2002
CIMNE

The CEPA, an Evolutionary Algorithm that preserves diversity by finding clusters in the population, has had its convergence performance improved by a technique tentatively called ‘evolutionary operator selection’. Performance is compared to results found in the literature, though at the moment it is not entirely clear how the evolutionary operator selection mechanisms work. The resulting algorithm has been applied to a number of problems - including a hybrid vehicle configuration and coke production in Shanxi Province, China.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

[LENI-CONF-2002-019].pdf

Access type

openaccess

Size

157.53 KB

Format

Adobe PDF

Checksum (MD5)

4298375896e4b6a4d4c13dc5648c7ddc

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés