Result: Multiobjective optimization using evolutionary algorithms : A comparative case study

Title:
Multiobjective optimization using evolutionary algorithms : A comparative case study
Authors:
Source:
PPSN V : parallel problem solving from nature (Amsterdam, 27-30 September 1998)Lecture notes in computer science. :292-301
Publisher Information:
Berlin: Springer, 1998.
Publication Year:
1998
Physical Description:
print, 12 ref
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Swiss Federal Institute of Technology Zurich, Computer Engineering and Communication Networks Laboratory (TIK), Gloriastrasse 35, 8092 Zurich, Switzerland
ISSN:
0302-9743
Rights:
Copyright 1999 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems

Operational research. Management
Accession Number:
edscal.1569259
Database:
PASCAL Archive

Further Information

Since 1985 various evolutionary approaches to multiobjective optimization have been developed, capable of searching for multiple solutions concurrently in a single run. But the few comparative studies of different methods available to date are mostly qualitative and restricted to two approaches. In this paper an extensive, quantitative comparison is presented, applying four multiobjective evolutionary algorithms to an extended 0/1 knapsack problem.