Multiobjective Optimization

Ke-Lin Du () and M. N. S. Swamy ()
Additional contact information
Ke-Lin Du: Xonlink Inc
M. N. S. Swamy: Concordia University, Department of Electrical and Computer Engineering

Chapter Chapter 23 in Search and Optimization by Metaheuristics, 2016, pp 371-412 from Springer

Abstract: Abstract Multiobjective optimization problems (MOPs) involve several conflicting objectives to be optimized simultaneously. The challenge is to find a Pareto set involving nondominated solutions that are evenly distributed along the Pareto Front. Metaheuristics for multiobjective optimization have been established as efficient approaches to solve MOPs.

Keywords: Pareto Front; Multiobjective Optimization; Pareto Optimal Solution; Pareto Frontier; Pareto Optimal Front (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:sprchp:978-3-319-41192-7_23

Ordering information: This item can be ordered from
http://www.springer.com/9783319411927

DOI: 10.1007/978-3-319-41192-7_23

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().