有没有办法定义多个"不等式约束"在R?
的nloptr
包中
不平等函数需要有五个不等式约束;矩阵的colsum(从整数向量堆叠)< = 1。 (6列中的5列)
这是我实现它的方式:
constraint.func <- function(my.data.var)
{
column = 2
constr <- c("numeric",ncol(my.data.matrix.inj) )
for(index in 1:ncol(my.data.matrix.inj)) #1 to 5
{
constr[index] <- sum(my.data.var[column], my.data.var[column+6], my.data.var[column+12], my.data.var[column+18])-1
column = column+1
}
constr.1 <- c(constr[1],constr[2],constr[3],constr[4],constr[5])
return(constr.1)
}
my.data.var
是数字向量,以矩阵形式堆叠。
my.data.var <- c(10,0.25,0.25,0.25,0.25,0.25,
10,0.25,0.25,0.25,0.25,0.25,
10,0.25,0.25,0.25,0.25,0.25,
10,0.25,0.25,0.25,0.25,0.25)
my.data.var
NLOPTR定义如下,但是当我运行它时,它表示&#34;不等式约束的数量= 0&#34;。
opts = list("algorithm"="NLOPT_LN_COBYLA",
"xtol_rel"=1.0e-5, "maxeval"=500)
result <- nloptr(my.data.var,eval_f = Error.func,lb=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
ub = (Inf,1,1,1,1,1,Inf,1,1,1,1,1,Inf,1,1,1,1,1,Inf,1,1,1,1,1),
eval_g_ineq=constraint.func,opts = opts)
print(result)
更新的答案: 我将Constraint.func定义为
constraint.func <- function(my.data.var)
{
column = 2
constr <- vector("numeric",length = 5)
for(index in 1:ncol(my.data.matrix.inj))
{
constr[index] <- sum(my.data.var[column], my.data.var[column+6], my.data.var[column+12], my.data.var[column+18])-1
column = column+1
}
return(constr)
}
答案 0 :(得分:3)
我更新了 Constraint.func ,现在 nloptr
选择了不等式约束。
constraint.func <- function(my.data.var)
{
column = 2
constr <- vector("numeric",length = 5)
for(index in 1:ncol(my.data.matrix.inj))
{
constr[index] <- sum(my.data.var[column], my.data.var[column+6], my.data.var[column+12], my.data.var[column+18])-1
column = column+1
}
return(constr) }
答案 1 :(得分:1)
我知道这已经晚了好几年了,但我最近也遇到了这个问题,似乎 eval_g_ineq
可以返回一个约束值向量:
library(nloptr)
# objective function
eval_f0 <- function( x, a, b ){return( sqrt(x[2]) )}
# constraint functions
eval_g0 <- function( x, a, b ) {
g1 <- (a*x[1] + b)^3 - x[2] ^2
g2 <- (a*x[1] + 2 * b)^3 - x[2]
return( c(g1, g2) )
}
a <- c(2,-1)
b <- c(0, 1)
x0 <- c(1.234,5.678)
# Solve using NLOPT_LN_COBYLA without gradient information
res1 <- nloptr( x0=x0 ,
eval_f=eval_f0,
lb = c(-Inf,0),
ub = c(Inf,Inf),
eval_g_ineq = eval_g0,
opts = list("algorithm" = "NLOPT_LN_COBYLA",
"xtol_rel" = 1e-8,
"maxeval" = 1e4,
"print_level" = 2),
a = a,
b = b )
print( res1 )