Archivers for the representation of the set of approximate solutions for MOPs

O. Schütze (), C. Hernández (), E-G. Talbi (), J. Q. Sun (), Y. Naranjani () and F.-R. Xiong ()
Additional contact information
O. Schütze: Cinvestav-IPN
C. Hernández: Cinvestav-IPN
E-G. Talbi: University of Lille 1
J. Q. Sun: University of California
Y. Naranjani: University of California
F.-R. Xiong: Tianjin University

Journal of Heuristics, 2019, vol. 25, issue 1, No 3, 105 pages

Abstract: Abstract In this paper we address the problem of computing suitable representations of the set of approximate solutions of a given multi-objective optimization problem via stochastic search algorithms. For this, we will propose different archiving strategies for the selection of the candidate solutions maintained by the generation process of the stochastic search process, and investigate them further on analytically and empirically. For all archivers we will provide upper bounds on the approximation quality as well as on the cardinality of the limit solution set. We conclude this work by a comparative study on some test problems in order to visualize the effect of all novel archiving strategies.

Keywords: Multi-objective optimization; Pareto set; Approximate solutions; Convergence; Stochastic search algorithm (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s10732-018-9383-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joheur:v:25:y:2019:i:1:d:10.1007_s10732-018-9383-z

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10732

DOI: 10.1007/s10732-018-9383-z

Access Statistics for this article

Journal of Heuristics is currently edited by Manuel Laguna

More articles in Journal of Heuristics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().