.png){kind=icon}
.png){kind=icon}
Return
A new filled function algorithm for constrained global optimization problems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.amc.2010.12.070.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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. (C) 2010 Elsevier Inc. All rights reserved.
Keywords:
Constrained global optimization problems
Filled function algorithm
Minimizer
Adjustable parameter
Numerical results
Journal
IF:
3.4
Papers:
2.3W
Citations:
3.3W