r如何使用lpSolve并限制选择的行

Question

我正在尝试在R中复制Excel求解器模型。这是一个简单的问题，开始寻求最大化点，而唯一的限制是限制了可以播放的事件数。 因此，我有一个两栏的数据框，其中包含比赛编号和项目积分。 在Excel中，我们有一个Play Yes / no二进制列，并将其乘以点并将其设置为最大值，从而允许模型将Play Yes / No列更改为0或1。约束条件限制了play yes / no变量的总和。到约束值，例如25。

library(lpSolve)
tournament<-rep(1:48,1)
mean<-c(12.2,30.4,30.9,44.1,31.3,27.6,31.5,25.0,31.2,24.0,28.0,23.9,14.1,9.5,17.2,37.8,30.5,43.0,32.1,30.7,30.2,37.0,32.1,28.9,23.7,4.6,29.0,29.1,30.7,31.6,49.5,25.1,30.2,10.3,30.3,21.8,88.5,31.0,30.9,2.9,31.1,30.3,29.7,63.7,31.6,91.6,30.6,31.0)

aggdata<-data.frame(tournament,mean)

maxevents <-25

obj<-aggdata$mean
con <- rep(1,nrow(aggdata))
dir <- c("==")
rhs <- maxevents
result <- lp("max", obj, con, dir, rhs, all.bin = TRUE)

结果仅查看数据帧的3行，应该查看数据的前25行。最终，我将添加其他约束，因为我知道此简单示例不需要lp，但需要首先克服此障碍。

Answer 1

希望这可以帮助！

library(lpSolve)

#objective function
obj <- rep(1, nrow(aggdata))

#constraints
con <- matrix(c(obj <- rep(1, nrow(aggdata)),
                as.vector(aggdata$point)), nrow = 2, byrow = T)  #you can add another constraints here and make 'nrow' equals to number of total constraints
dir <- c("==", "<=")
rhs <- c(25,     #total number of tournament
         1000)   #let's assume that total points can't exceeds 1000

#optimization solution
result <- lp ("max", obj, con, dir, rhs, all.bin=TRUE)
result$solution

样本数据：

aggdata <- data.frame(tournament = rep(1:48,1),
                      point = c(12.2,30.4,30.9,44.1,31.3,27.6,31.5,25.0,31.2,24.0,28.0,23.9,14.1,
                               9.5,17.2,37.8,30.5,43.0,32.1,30.7,30.2,37.0,32.1,28.9,23.7,4.6,
                               29.0,29.1,30.7,31.6,49.5,25.1,30.2,10.3,30.3,21.8,88.5,31.0,30.9,
                               2.9,31.1,30.3,29.7,63.7,31.6,91.6,30.6,31.0))
#  tournament point
#1          1  12.2
#2          2  30.4
#3          3  30.9
#4          4  44.1
#5          5  31.3
#6          6  27.6