# Optimization in R similar to MS Excel Solver

4 messages
Open this post in threaded view
|

## Optimization in R similar to MS Excel Solver

 This post was updated on . CONTENTS DELETED The author has deleted this message.
Open this post in threaded view
|

## Re: Optimization in R similar to MS Excel Solver

 On 11-03-2013, at 23:31, Pavel_K <[hidden email]> wrote: > Dear all, > I am trying to find the solution for the optimization problem focused on the > finding minimum cost. > I used the solution proposed by excel solver, but there is a restriction in > the number of variables. > > My data consists of 300 rows represent cities and 6 columns represent the > centres. It constitutes a cost matrix, where the cost are distances between > each city and each of six centres. > ..+ 1 column contains variables, represents number of firms. > I want to calculate the minimum cost between cities and centres.  Each city > can belong only to one of the centres. > > A model example: > costs: distance between municipalities and centres + plus number of firms in > each municipality > "Municipality" "Centre1" "Centre2" "Centre3" "Centre4" "Centre5" "Centre6" > "Firms" > "Muni1"            30    20            60              40             > 66             90            15 > "Muni2"            20    30                  60              40             > 66             90            10 > "Muni3"            25    31            60              40             > 66             90              5 > "Muni4"            27    26            60              40             > 66             90             30 > > The outcome of excel functon Solver is: > cost assigned > "Municipality" "Centre1" "Centre2" "Centre3" "Centre4" "Centre5" "Centre6" > "Solution" > "Muni1"            0            20               0                0               > 0                0            300 > "Muni2"            20     0                     0                0               > 0                0            200 > "Muni3"            25     0                       0                0               > 0                0            125 > "Muni4"              0    26               0                0               > 0                0            780 > > objective : 1405 > > I used package "lpSolve" but there is a problem with variables "firms": > > s <- as.matrix(read.table("C:/R/OPTIMALIZATION/DATA.TXT", dec = ",", > sep=";",header=TRUE)) > >      [2] [3] [4] [5] [6] > [1] 30 20 60 40 66 90 > [2] 20 30 60 40 66 90 > [3] 25 31 60 40 66 90 > [4] 27 26 60 40 66 90 > > row.signs <- rep ("=", 4) > row.rhs <- c(15,10,5,30) > col.signs <- rep ("=", 6) > col.rhs <- c(1,1,1,1,1,1) > lp.transport (costs, "min", row.signs, row.rhs, col.signs, col.rhs, > presolve=0, compute.sens=0) > lp.transport (costs, "min", row.signs, row.rhs, col.signs, col.rhs, > presolve=0, compute.sens=0)\$solution > > Outcome: > Error in lp.transport(costs, "min", row.signs, row.rhs, col.signs, col.rhs, > : >  Error: We have 6 signs, but 7 columns > > Does anyone know where could the problem ? > Does there exist any other possibility how to perform that analysis in R ? > I am bit confused here about how can I treat with the variables "firms". Please provide a reproducible example including the necessary library() statements. In the call of lp.transport you are using a variable "costs" but where is it defined? You read a file with read.table into a variable "s". Use dput. Berend   ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.