mixtureRangeOptim {MixOptim}

Performs a specific range optimization

Description

This function performs an optimization testing within an interval defined by the user using alpha values for each middle point provided. It allows the generation of the data frame required for plotting.

Usage

mixtureRangeOptim(
  functions,
  desirabilityModel,
  midPoints,
  alpha,
  step = 0.01,
  plot = TRUE,
  verbose = TRUE
)

Arguments

functions

An array of functions

desirabilityModel

A desirability overallD model

midPoints

An array with the references (mid-points) for the optimization

alpha

Defines the range of the seach, as startPoint +- alpha for each x value

step

The ammount of each increment in the optimization

plot

Define is the data frame that can be used for the desirabilityPlot function will be create. Strongly affects performance

verbose

Defines if the user should be updated with the processing status (percentages)

Value

A list containg the data regarding the maximum desirability found

Examples

library(MixOptim)
dados <- read.table(header = TRUE, sep = "\t", text = "
ID	TiO2	Vehicle	Extender A	Extender B	Hiding	Scrub
1	0.05	0.20	0.30	0.45	7.8953	533.67
2	0.45	0.20	0.30	0.05	32.862	749
3	0.05	0.60	0.30	0.05	3.721	39.5
4	0.05	0.20	0.70	0.05	9.2751	203.25
5	0.25	0.20	0.30	0.25	20.132	555.25
6	0.05	0.40	0.30	0.25	4.7137	51.75
7	0.05	0.20	0.50	0.25	8.3829	342.75
8	0.25	0.40	0.30	0.05	16.245	84.75
9	0.25	0.20	0.50	0.05	22.639	360.75
10	0.05	0.40	0.50	0.05	5.4645	48
11	0.05	0.33	0.43	0.18	5.8882	76
12	0.18	0.20	0.43	0.18	17.256	386.25
13	0.18	0.33	0.30	0.18	12.351	136
14	0.18	0.33	0.43	0.05	14.499	75.5
15	0.10	0.25	0.35	0.30	10.548	325.75
16	0.30	0.25	0.35	0.10	22.096	359
17	0.10	0.45	0.35	0.10	6.2888	40.75
18	0.10	0.25	0.55	0.10	10.629	136.67
19	0.15	0.30	0.40	0.15	11.777	114")

hiding<-function(x) 67.748*x[1] + 7.291*x[2] + 11.419*x[3] + 14.578*x[4] -
   64.32*x[1]*x[2] + 35.878*x[1]*x[3] - 15.696*x[1]*x[4] - 31.006*x[2]*x[3] -
   38.668*x[2]*x[4] - 6.59*x[3]*x[4]
scrub<-function(x) 3937.5*x[1] + 899.3*x[2] + 502*x[3] + 2354.8*x[4] -
   8227.2*x[1]*x[2] - 3227.4*x[1]*x[3] - 2447.7*x[1]*x[4] - 2435.3*x[2]*x[3] -
   6325.1*x[2]*x[4] - 1050.3*x[3]*x[4]

funcoes2 <- c(hiding, scrub)
des1<-dMax(min(dados$Hiding), max(dados$Hiding))
des2<-dMin(min(dados$Scrub), max(dados$Scrub))
finalD<-dOverall(des1, des2)

# code commented due to process time requirement
#teste <- mixtureRangeOptim(funcoes2, finalD, midPoints = c(0.25, 0.4, 0.5, 0.25),
#    alpha = c(0.2, 0.2, 0.2, 0.2), step = 0.01, plot = TRUE)
#desirabilityPlot(funcoes2, teste$plotData, teste$bestComposition, list(des1, des2),
#    c("max", "min"))
#teste2 <- mixtureRangeOptim(funcoes2, finalD, midPoints = teste$bestComposition,
#    alpha = c(0.01, 0.01, 0.01, 0), step = 0.001, plot = FALSE)
#teste2
#desirabilityPlot(funcoes2, teste$plotData, teste2$bestComposition, list(des1, des2),
#    c("max", "min"))