iterate_EPIC_NM: Performs one iteration of EPIC algorithm

In ingridas/EPICR: An Implementation of Efficient Pareto Iterative Classification Method

Description

Performs one iteration of EPIC algorithm

Usage

iterate_EPIC_NM(wv, i, con, L, U, p.next, p.pareto, strategy, iter, absmin,
  absmax, local.search)

Arguments

wv	- a weighting vector
i	- iteration number
con	- constraints, an analytical function cheap to evaluate, in a form g_i(x)>=0, if available; otherwise it is equal to FALSE
L	- row vector of lower bounds of the design space
U	- row vector of upper bounds of the design space
p.next	- probability used to select a next decision vector
p.pareto	- indicator used to assign points to one of the set: dominated or nondominated
strategy	- strategy used to select the nex vector to evaluate
iter	- a list conatinig information related with the current algorithm iteration
absmin	- the estimate of minimum values of objective functions (if not provided we will use the min value of Y)
absmax	- the estimate of maximum values of objective functions (if not provided we will use the max value of Y)
local.search	- indicates what EPIC version will be run. TRUE - enhanced EPIC version,FALSE - the original one. DEFAULT = TRUE.

Value

iter - an updated list

ingridas/EPICR documentation built on May 18, 2019, 4:54 a.m.