Dynamic Objectives Aggregation in Multi-objective Evolutionary Optimization
AbstractSeveral approaches for solving multi-objective optimization problems entail a form of scalarization of the objectives. This paper proposes a study of different dynamic objectives aggregation methods in the context of evolutionary algorithms. These methods are mainly based on both weighted sum aggregations and curvature variations. A comparison analysis is presented on the basis of a campaign of computational experiments on a set of benchmark problems from the literature.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia in its series Quaderni DSEMS with number 06-2008.
Length: 13 pages
Date of creation: Mar 2008
Date of revision:
Multi-objective optimization; Evolutionary algorithms; Aggregate objective functions;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-10-13 (All new papers)
- NEP-CMP-2008-10-13 (Computational Economics)
- NEP-EVO-2008-10-13 (Evolutionary Economics)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Luca Grilli).
If references are entirely missing, you can add them using this form.