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On 11032013, 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
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https://stat.ethz.ch/mailman/listinfo/rhelpPLEASE do read the posting guide http://www.Rproject.org/postingguide.htmland provide commented, minimal, selfcontained, reproducible code.


Pavel_K <kuk064 <at> vsb.cz> writes:
>
> 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.
(1) The solution you say the Excel Solver returns does not appear to be
correct: The column sum in columns 3 to 5 is not (greater or) equal
to 1 as you request.
(2) lpSolve does not return an error, but says "no feasible solution found",
which seems to be correct: The equality constraints are too strict.
(3) If you relieve these constraints to inequalities, lpSolves does find
a solution:
costs < matrix(c(
30, 20, 60, 40, 66, 90,
20, 30, 60, 40, 66, 90,
25, 31, 60, 40, 66, 90,
27, 26, 60, 40, 66, 90), 4, 6, byrow = TRUE)
firms < c(15, 10, 5, 30)
row.signs < rep (">=", 4)
row.rhs < firms
col.signs < rep (">=", 6)
col.rhs < c(1,1,1,1,1,1)
require("lpSolve")
T < lp.transport (costs, "min", row.signs, row.rhs, col.signs, col.rhs,
presolve = 0, compute.sens = 0)
T$solution
sum(T$solution * costs) # 1557
Of course, I don't know which constraints you really want to impose.
Hans Werner
> 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, ...):
> 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".
>
> Thanks
> Pavel
>
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https://stat.ethz.ch/mailman/listinfo/rhelpPLEASE do read the posting guide http://www.Rproject.org/postingguide.htmland provide commented, minimal, selfcontained, reproducible code.


On 12032013, at 08:45, Pavel_K < [hidden email]> wrote:
> Dear Mr Hasselman,
> for a better understanding I have attached an example solved in excel by
> using the tool Solver.
>
> I want to assign for each municipality one of the centres and apply it for
> calculating the minimum cost as you can see in an example.
> I used package lpsolve, but it does not work. I am not sure how to treat
> with this part of statement, I think I made mistake in it:
> row.rhs < c(15,10,5,30) and
> col.rhs < c(1,1,1,1,1,1)
>
> The example in R:
>
> library(lpSolve)
> costs < as.matrix(read.table("C:/R/OPTIMIZATION/DATA.TXT", dec = ",",
> sep=";",header=TRUE))
> 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
> Hope the example solved in excel will help you to understand my problem.
>
You post is not available on Nabble.
The excel file is inaccessible because it doesn't exist.
Apart from that: show the contents of costs.
Use
dput(costs)
and put the result in the message to Rhelp. That is the only way one can find out why lp.transport gives an error.
And please read the posting guide (link is at the bottom of each posting to this list).
Berend
______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/rhelpPLEASE do read the posting guide http://www.Rproject.org/postingguide.htmland provide commented, minimal, selfcontained, reproducible code.

