essR-package


	  essR attempts to solve problems of the form:
 
	<code>
	min F(x)  subject to: 
	x
		ceq(x) = 0 (equality constraints)
		c_L <= c(x)="" <="c_U" (inequality="" constraints)="" x_l="" (bounds="" on="" the="" decision="" variables)="" code="">
          Constraint functions, if applicable, must be declared in the same script as the objective function as a second output argument, e.g.:
	<code>
 	 	 myfunction &lt;- function(x){
				calculate fx - scalar containing the objective function value
				calculate gx - vector (or empty) containing the constraints values
				return(list(fx,gx))
		}
	</code>
</=></code>

optimization

 package

search

scatter

Jose Egea

MEIGOR

MEIGO - MEtaheuristics for bIoinformatics Global Optimization

essR-package function

essR attempts to solve problems of the form:
 
	<verb>min F(x)  subject to: 
	x
		ceq(x) = 0 (equality constraints)
		c_L <= c(x) <= c_U (inequality constraints)
		x_L <= x <= x_U (bounds on the decision variables)</verb>
          Constraint functions, if applicable, must be declared in the same script as the objective function as a second output argument, e.g.:
	<verb>myfunction <- function(x){
				calculate fx - scalar containing the objective function value
				calculate gx - vector (or empty) containing the constraints values
				return(list(fx,gx))
		}</verb>

Global optimization algorithm for MINLPs based on Scatter Search

essR-package: Global optimization algorithm for MINLPs based on Scatter Search

Description

Arguments

Details

References

See Also