A new filled function algorithm for constrained global optimization problems

A new filled function with one parameter is proposed for solving constrained global optimization problems without the coercive condition, in which the filled function contains neither exponential term nor fractional term and is easy to be calculated. A corresponding filled function algorithm is esta...

Full description

Saved in:
Bibliographic Details
Published in:Applied mathematics and computation Vol. 217; no. 12; pp. 5853 - 5859
Main Authors: He, Suxiang, Chen, Weilai, Wang, Hui
Format: Journal Article
Language:English
Published: Amsterdam Elsevier Inc 15.02.2011
Elsevier
Subjects:
Adjustable parameter
Algorithms
Coercive force
Computation
Constrained global optimization problems
Constraints
Exact sciences and technology
Filled function algorithm
Mathematical analysis
Mathematical models
Mathematics
Minimizer
Numerical analysis
Numerical analysis. Scientific computation
Numerical results
Optimization
Sciences and techniques of general use
Special functions
Minimizer
Filled function algorithm
Constrained global optimization problems
Numerical results
Adjustable parameter
Optimization method
Algorithm
Exponential function
Constrained optimization
Numerical analysis
Algorithm performance
Applied mathematics
Problem solving
Algorithm analysis
ISSN:0096-3003, 1873-5649
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A new filled function with one parameter is proposed for solving constrained global optimization problems without the coercive condition, in which the filled function contains neither exponential term nor fractional term and is easy to be calculated. A corresponding filled function algorithm is established based on analysis of the properties of the filled function. At last, we perform numerical experiments on some typical test problems using the algorithm and the detailed numerical results show that the algorithm is effective.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2010.12.070