linearprogramming/.Rhistory at master · jmsallan/linearprogramming · GitHub

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setwd("~/Documents/linearprogramming")
source("CapFacility.R")
d <- c(100, 200, 200, 150, 200)
s <- c(1200, 800)
f <- c(3000, 3000)
CapFacility(d, s, f, c)
c <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5 )
c
source("CapFacility.R")
demand <- c(100, 200, 200, 150, 200)
capacity <- c(1200, 800)
fixed.costs <- c(3000, 3000)
transp.costs <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5)
CapFacility(demand, capacity, fixed.costs, transp.costs)
plan <- CapFacility(demand, capacity, fixed.costs, transp.costs)
solution <- as.matrix(plan$solution, 2, 5, byrow=TRUE)
solution
solution <- as.matrix(plan$solution, 2, 5)
solution
solution <- as.matrix(plan$solution[1:10], 2, 5)
solution
?as.matrix
as.matrix(1:10, 2, 5)
as.matrix(1:10, nrow=2, ncol=5)
as.matrix(1:4, 2, 2)
dim(plan$solution[1:10]) <- c(2,5)
plan$solution
plan <- CapFacility(demand, capacity, fixed.costs, transp.costs)
plan
source("CapFacility.R")
source("CapFacility.R")
plan <- CapFacility(demand, capacity, fixed.costs, transp.costs)
plan
source("CapFacility.R")
plan <- CapFacility(demand, capacity, fixed.costs, transp.costs)
plan
sum(demand)
source("CapFacility.R")
demand <- c(100, 200, 200, 150, 200)
capacity <- c(1200, 800)
fixed.costs <- c(3000, 3000)
transp.costs <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5,byrow=TRUE)
plan <- CapFacility(demand, capacity, fixed.costs, transp.costs)
plan
demand <- c(200, 400, 300, 450, 300)
sum(demand)
demand.B <- c(200, 400, 300, 450, 300)
capacity <- c(1200, 800)
fixed.costs <- c(3000, 3000)
transp.costs <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5,byrow=TRUE)
plan.caseB <- CapFacility(demand.B, capacity, fixed.costs, transp.costs)
plan.B <- CapFacility(demand.B, capacity, fixed.costs, transp.costs)
plan.B
demand.C <- c(200, 400, 300, 450, 300)
capacity.C <- c(1000, 600)
fixed.costs <- c(3000, 3000)
transp.costs <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5,byrow=TRUE)
plan.C <- CapFacility(demand.B, capacity, fixed.costs, transp.costs)
plan.C
plan.C <- CapFacility(demand.C, capacity.C, fixed.costs, transp.costs)
plan.C
rm(list=ls())
source("CapFacility.R")
#model parameters (case A)
demand <- c(100, 200, 200, 150, 200)
capacity <- c(1200, 800)
fixed.costs <- c(3000, 3000)
transp.costs <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5,byrow=TRUE)
#the solution is stored in the plan variable
plan.caseA <- CapFacility(demand, capacity, fixed.costs, transp.costs)
#model parameters (case B)
demand.B <- c(200, 400, 300, 450, 300)
capacity <- c(1200, 800)
fixed.costs <- c(3000, 3000)
transp.costs <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5,byrow=TRUE)
plan.B <- CapFacility(demand.B, capacity, fixed.costs, transp.costs)
#model parameters (case C):non-feasible solution
demand.C <- c(200, 400, 300, 450, 300)
capacity.C <- c(1000, 600)
fixed.costs <- c(3000, 3000)
transp.costs <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5,byrow=TRUE)
#non-feasible solution: plan.C$status equals one, all other variables of plan.C zero
plan.C <- CapFacility(demand.C, capacity.C, fixed.costs, transp.costs)
rm(list=ls())
#example of use of the CapFaciliy function
#loading the function
source("CapFacility.R")
#model parameters (case A)
demand <- c(100, 200, 200, 150, 200)
capacity <- c(1200, 800)
fixed.costs <- c(3000, 3000)
transp.costs <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5,byrow=TRUE)
#the solution is stored in the plan variable
plan.A <- CapFacility(demand, capacity, fixed.costs, transp.costs)
#model parameters (case B)
demand.B <- c(200, 400, 300, 450, 300)
capacity <- c(1200, 800)
fixed.costs <- c(3000, 3000)
transp.costs <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5,byrow=TRUE)
plan.B <- CapFacility(demand.B, capacity, fixed.costs, transp.costs)
#model parameters (case C):non-feasible solution
demand.C <- c(200, 400, 300, 450, 300)
capacity.C <- c(1000, 600)
fixed.costs <- c(3000, 3000)
transp.costs <- matrix(c(1,4,5,6,6,4,3,7,6,9),2,5,byrow=TRUE)
#non-feasible solution: plan.C$status equals one, all other variables of plan.C zero
plan.C <- CapFacility(demand.C, capacity.C, fixed.costs, transp.costs)
install.packages("Rsymphony")
SolverLP <- function(model, method="CPLEX_LP", decimal=0){
library(Rglpk)
model1.lp <- Rglpk_read_file(model, type = method, verbose=F)
model1.lp.sol <- Rglpk_solve_LP(model1.lp$objective, model1.lp$constraints[[1]], model1.lp$constraints[[2]], model1.lp$constraints[[3]], model1.lp$bounds, model1.lp$types, model1.lp$maximum)
library(xtable)
model1.lp.sol.df <- as.data.frame(model1.lp.sol$solution)
model1.lp.sol.df <- rbind(model1.lp.sol.df, c(model1.lp.sol$optimum))
rownames(model1.lp.sol.df) <- c(attr(model1.lp, "objective_vars_names"),"obj")
colnames(model1.lp.sol.df) <- "Solution"
table.sol <- xtable(model1.lp.sol.df, digits=decimal)
results <- list(sol=model1.lp.sol, df=model1.lp.sol.df, latex=table.sol)
return(results)
}
setwd("~/Documents/linearprogramming")
SolverLP("PO3_a.mod")
SolverLP("PO4.mod")
setwd("~/Documents/linearprogramming")
library(Rglpk)
Rglpk_read_file("P03_b.mod")
Rglpk_read_file("P03_b.mod", method="CPLEX_LP")
?Rglpk_read_file
Rglpk_read_file("P03_b.mod", type ="CPLEX_LP")
SolverLP("P03_b.mod")
install.packages("xtable")
SolverLP("P03_b.mod")
SolverLP("ProdAmpl.mod", "MathProg")
library(xtable)
?xtable