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Golp is a Golang wrapper for the LPSolve linear (and integer) programming library.

Installation

Step 1: Get the golp Go code

go get -d github.com/draffensperger/golp

Step 2: Get the LPSolve library

Golp is configured to dynamically link to LPSolve and expects lpsolve to reside in the following places:

Mac: /opt/local/includes/lpsolve && /opt/local/lib which is where ports puts it.

Linux (general): $GOPATH/src/github.com/draffensperger/golp/lpsolve.

Windows (general): $GOPATH/src/github.com/draffensperger/golp@xxx/lpsolve.

You will need an LPSolve library suitable for your operating system, which you can get from SourceForge.

Here's how you could download the LPSolve library for 64-bit windows:

https://sourceforge.net/projects/lpsolve/files/lpsolve/5.5.2.0/lp_solve_5.5.2.0_dev_win64.zip/download

Then extract content zip file in $GOPATH/src/github.com/draffensperger/golp@xxx/lpsolve. Finally, copy lpsolve55.dll file into your golang project directory (or maybe into c:\windows\system32).

To install LPSolve on Mac OS X, install MacPorts, then run sudo port install lp_solve.

Here's how you could download and extract the LPSolve library for 64-bit Linux:

LP_URL=http://sourceforge.net/projects/lpsolve/files/lpsolve/5.5.2.0/lp_solve_5.5.2.0_dev_ux64.tar.gz
LP_DIR=$GOPATH/src/github.com/draffensperger/golp/lpsolve
mkdir -p $LP_DIR
curl -L $LP_URL | tar xvz -C $LP_DIR

On Debian 8+ you can install the lpsolve package with sudo apt-get install liblpsolve55-dev and then set the environment variables for LDFLAGS and CFLAGS like:

export CGO_CFLAGS="-I/usr/include/lpsolve"
export CGO_LDFLAGS="-llpsolve55 -lm -ldl -lcolamd"

With some configuration changes, it would be possible to statically link to LPSolve but that may have licensing/distribution implications for your project since LP Solve is LGPL licensed.

Usage

Not all LPSolve functions are supported, but it's currently possible to run a simple linear and integer program using golp. For details, see the golp GoDoc page.

Feel free to open a GitHub issue or pull request if you'd like more functions added.

Example with real-valued variables

The example below in an adaption of an example in the LP Solve documentation. for maximizing a farmer's profit.

package main

import "fmt"
import "github.com/draffensperger/golp"

func main() {
  lp := golp.NewLP(0, 2)
  lp.AddConstraint([]float64{110.0, 30.0}, golp.LE, 4000.0)
  lp.AddConstraint([]float64{1.0, 1.0}, golp.LE, 75.0)
  lp.SetObjFn([]float64{143.0, 60.0})
  lp.SetMaximize()

  lp.Solve()
  vars := lp.Variables()
  fmt.Printf("Plant %.3f acres of barley\n", vars[0])
  fmt.Printf("And  %.3f acres of wheat\n", vars[1])
  fmt.Printf("For optimal profit of $%.2f\n", lp.Objective())

  // No need to explicitly free underlying C structure as golp.LP finalizer will
}

Outputs:

Plant 21.875 acres of barley
And  53.125 acres of wheat
For optimal profit of $6315.62

MIP (Mixed Integer Programming) example

LPSolve also supports setting variables to be integral or binary and uses the branch-and-bound algorithm for such problems. This example is from the LPSolve integer variables documentation.

import "fmt"
import "github.com/draffensperger/golp"

func main() {
  lp := golp.NewLP(0, 4)
  lp.AddConstraintSparse([]golp.Entry{{0, 1.0}, {1, 1.0}}, golp.LE, 5.0)
  lp.AddConstraintSparse([]golp.Entry{{0, 2.0}, {1, -1.0}}, golp.GE, 0.0)
  lp.AddConstraintSparse([]golp.Entry{{0, 1.0}, {1, 3.0}}, golp.GE, 0.0)
  lp.AddConstraintSparse([]golp.Entry{{2, 1.0}, {3, 1.0}}, golp.GE, 0.5)
  lp.AddConstraintSparse([]golp.Entry{{2, 1.0}}, golp.GE, 1.1)
  lp.SetObjFn([]float64{-1.0, -2.0, 0.1, 3.0})
  lp.SetInt(2, true)
  lp.Solve()

  fmt.Printf("Objective value: %v\n", lp.Objective())
  vars := lp.Variables()
  fmt.Printf("Variable values:\n")
  for i := 0; i < lp.NumCols(); i++ {
    fmt.Printf("x%v = %v\n", i + 1, vars[i])
  }
}

Outputs:

Objective value: -8.133333333333333
Variable values:
x1 = 1.6666666666666665
x2 = 3.333333333333333
x3 = 2
x4 = 0

Alternative linear / mixed integer solver libraries

There are also Go bindings for the GPL-licensed GNU Linear Programming Kit (GLPK) at github.com/lukpank/go-glpk.

The Google or-tools project provides a C++ SWIG compatible inteface for a number of other linear and mixed integer solvers like CBC, CLP, GLOP, Gurobi, CPLEX, SCIP, and Sulum. There is Go support for SWIG bindings, so it should be possible to write a wrapper that would connect to those other solvers via the or-tools library as well.

Acknowledgements and License

The LPSolve library this project depends on is LGPL licensed.

The stringbuilder.c code is from breckinloggins/libuseful.

Thanks to Mike Gaffney (gaffo) for correcting the Linux install instructions. Thanks to khaaan for a typo fix and Debian 8 install instructions.

The golp Go code is MIT licensed as follows:

The MIT License (MIT)

Copyright (c) 2015 David Raffensperger

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.