R中的NSGA2遗传算法

我正在研究R（库mco）上的NSGA2包

我的NSGA2代码需要永远运行，所以我想知道：

1）有没有办法限制解数值的精度（比如，可能高达小数点后3位），而不是无限大？

2）如何设置相等约束（在线约束似乎都是>=或

VTR = get.hist.quote(instrument = 'VTR',
        start="2010-01-01",  end = "2015-12-31",
        quote = c("AdjClose"),provider = "yahoo",
        compress = "d") 

ObjFun1 <- function (xh){
    f1 <- sum(HSVaR_P(merge(VTR, CMI, SPLS, KSS, DVN, MAT, LOE, KEL, COH, AXP), xh, 0.05, 2))
    tempt = merge(VTR, CMI, SPLS, KSS, DVN, MAT, LOE, KEL, COH, AXP)
    tempt2 = tempt[(nrow(tempt)-(2*N)):nrow(tempt),]
    for (i in 1:nrow(tempt2))
    {
        for (j in 1:ncol(tempt2))
        {
        if (is.na(tempt2[i,j])) 
        {
        tempt2[i,j] = 0
        }
        }
    }
    f2 <- ((-1)*abs(sum((xh*t(tempt2)))))
    c(f1=f1,f2=f2)
}

Constr <- function(xh){ 
    totwt <- (1-sum(-xh))
    totwt2 <- (sum(xh)-1)
    c(totwt,totwt2)
}


Solution1 <- nsga2(ObjFun1, n.projects, 2,
                  lower.bounds=rep(0,n.projects), upper.bounds=rep(1,n.projects),
                  popsize=n.solutions,  constraints = Constr, cdim=1,
                  generations=generations)