The lp_solve Interface Toolbox for O-Matrix integrates
lpsolve, a free,
public domain linear programming solver with the O-Matrix
The lpsolve package solves pure linear,
mixed integer/binary, semi-continuous and special ordered sets models. lpsolve
has no limit on model size and has solved models with more than 100000 constraints.
Input can be loaded directly from O-Matrix,
from lp, xml or mps input files, and
from dynamically called modeling languages.
The lp_solve Interface Toolbox for O-Matrix is written completely
in the C programming language to provide maximum performance. The interface
uses the O-Matrix DLL linking capability to integrate seamlessly
into the O-Matrix language.
The integration of lpsolve with O-Matrix is a win-win situation
for both packages. For O-Matrix, lpsolve provides a toolbox to solve
Mixed Integer Linear Models in a very easy way. For lpsolve,
O-Matrix gives the solver toolbox a matrix interface and
- Peter Notebaert, lp_solve co-developer
The high-performance and efficiency of both O-Matrix
and lpsolve enable the solution of many problems whose size
and scope exceeds the abilities of most spreadsheet-based and
interactive solvers. Linear programming has become a common and
powerful tool for many facets of business, engineering and science.
Some application areas include:
Both the lpsolve package and The lp_solve Interface Toolbox for
O-Matrix are free, but require O-Matrix version 6.3 or greater.
The complete lpsolve package, the O-Matrix interface, documentation,
and several examples for getting started are included in the O-Matrix
trial which you may download at:
O-Matrix with lpsolve trial
- Production and Operations Management - Quite often in the
process industries a given raw material can be made into a wide variety of products.
Given the present profit margin on each product, determine the
quantities of each product that should be produced.
- Finance - The problem of the investor could be a portfolio-mix selection problem.
- Human Resources - Personnel planning problems can also be
analyzed with linear programming.
- Distribution - Determine the best shipping
patterns among numerous factories to minimize cost.
- Advertising - Determine the proper mix of media to use
in an advertising campaign.
- Scheduling - Given the starting time and duration of various
activities determine the optimal schedule and project completion