package lp-glpk
Install
Dune Dependency
Authors
Maintainers
Sources
md5=dad8525a3cef45b161698b17702a29a7
sha512=e8a36c0a87a763af6674db472dc8cf64a456eeb481cd215d9b08fc0eb59cba7e65c8df8d3d29597f65c14af63d1a93ae4843506f05aba69884006b6452c1a690
Description
This library helps the modeling of Linear Programming (LP) and Mixed Integer Programming (MIP) in OCaml. This package is an optional solver-interface to GLPK (GNU Linear Programming Kit).
Published: 14 Feb 2021
README
ocaml-lp : LP and MIP modeling in OCaml
This library helps the modeling of Linear Programming (LP) and Mixed Integer Programming (MIP) in OCaml. It supports the model with not only linear terms, but also quadratic terms. The model can be imported-from / exported-to CPLEX LP file format, which can be loaded by various solvers. It also has direct interfaces to some solvers. Currently supported are GLPK (GNU Linear Programming Kit) and Gurobi.
Install
# optional but recommended to pin dev-repo as it's on quite early stage of development
opam pin lp --dev-repo
opam pin lp-glpk --dev-repo
opam pin lp-gurobi --dev-repo # if you have an access to Gurobi
opam install lp lp-glpk # lp-gurobi
Example
A minimum example is shown below. More examples can be found on wiki.
let x = Lp.var "x"
let y = Lp.var "y"
let problem =
let open Lp in
let obj = maximize (x ++ y) in
let c0 = x ++ (c 1.2 *~ y) <~ c 5.0 in
let c1 = (c 2.0 *~ x) ++ y <~ c 1.2 in
make obj [c0; c1]
let write () = Lp.write "my_problem.lp" problem
let solve () =
(* For Gurobi, use Lp_gurobi instead *)
match Lp_glpk.solve problem with
| Ok (obj, xs) ->
Printf.printf "Objective: %.2f\n" obj ;
Printf.printf "x: %.2f y: %.2f\n"
(Lp.PMap.find x xs) (Lp.PMap.find y xs)
| Error msg ->
print_endline msg
let () =
if Lp.validate problem then (write () ; solve ())
else print_endline "Oops, my problem is broken."
Documentation
High level APIs have comments for odoc (or ocamldoc). Generated docs can be found online or in docs directory.
Notes on GLPK interface
To use this, compile your application with
-cclib -lglpk
flags.Since this is tested only on GLPK version 4.65 and 5+, something may fail on older versions.
Conformity to LP file format
Currently only basic features of LP file format are supported. Yet to be supported are advanced features, which are typically available on commercial solvers. (There is no standard of LP file, though.)
supported
Single objective (linear and quadratic)
Constraints (linear and quadratic)
Bounds
Variable types (general and binary integers)
not-supported
Semi-continuous variables
Multi-objective
Lazy constraint
Special ordered set (SOS)
Piecewise-linear (PWL) objective and constraint
General Constraint
Scenario
References
Some references to LP file format.
License
MIT