Name
Abstract | ||
|---|---|---|
Purpose - In this article the aim is to propose a new form to densify parallelepipeds of R-N by sequences of alpha-dense curves with accumulated densities. Design/methodology/approach - This will be done by using a basic alpha-densification technique and adding the new concept of sequence of alpha-dense curves with accumulated density to improve the resolution of some global optimization problems. Findings - It is found that the new technique based on sequences of alpha-dense curves with accumulated densities allows to simplify considerably the process consisting on the exploration of the set of optimizer points of an objective function with feasible set a parallelepiped K of R-N. Indeed, since the sequence of the images of the curves of a sequence of alpha-dense curves with accumulated density is expansive, in each new step of the algorithm it is only necessary to explore a residual subset. On the other hand, since the sequence of their densities is decreasing and tends to zero, the convergence of the algorithm is assured. Practical implications - The results of this new technique of densification by sequences of alpha-dense curves with accumulated densities will be applied to densify the feasible set of an objective function which minimizes the quadratic error produced by the adjustment of a model based on a beta probability density function which is largely used in studies on the transition-time of forest vegetation. Originality/value - A sequence of alpha-dense curves with accumulated density represents an original concept to be added to the set of techniques to optimize a multivariable function by the reduction to only one variable as a new application of alpha-dense curves theory to the global optimization. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1108/03684921211213151 | KYBERNETES |
Keywords | Field | DocType |
Alpha-dense curves,Sequence of alpha-dense curves with accumulated density,Beta probability density function,Global optimization | Convergence (routing),Residual,Mathematical optimization,Global optimization,Feasible region,Expansive,Mathematics,Parallelepiped | Journal |
Volume | Issue | ISSN |
41 | 1-2 | 0368-492X |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| G. Mora | 1 | 15 | 3.42 |
| J. C. Navarro | 2 | 0 | 0.34 |