| FortMP
Linear, Integer and (Mixed) Integer Programming Optimisation System
|
FortMP
has been widely deployed to solve many management
science and operational research problems. In its
basic configuration, FortMP is suitable for Linear,
and (Mixed) Integer Programming, but it is also
available in extended configurations for (Integer)
Quadratic Programming, and Stochastic Programming.
The full systems is also available as a parallel
computational platform.
|
 Designed
for a variety of Optimisation problems |
| |
FortMP is a state
of the art optimisation system designed to solve
a wide range of well known optimisation problems
including:
- Large Scale Linear Programming problems
- Variable Separable Programming problems including
special ordered sets of type 1 and type 2 (SOS1
and SOS2)
- Mixed integer programming problems with zero-one
as well as general integer variables.
FortMP has been succesfully deployed in a number
of Transportation, Scheduling, Chemical Engineering
Product Blending, Economic Modelling, Energy Systems
and Networks, Industrial Scheduling Applications
(among others) involving Linear or Discrete optimisation. |
| Computational
Algorithms |
| |
FortMP incorporates a
suite of well known solution algorithms that have
been carefully designed taking into consideration
underlying data structures and modular processing
components such that different features can interact
well with each other. Research and development of
the underlying algorithms started in the mid eighties.
However, the computational algorithms and the software
system have been constantly kept up to date with
the developments that continue to take place in
this field.
- Linear programming problems are processed
by sparse simplex (SSX) with both PRIMAL and
DUAL variants. An interior point method (IPM)
algorithm is also included which uses the PRIMAL-DUAL
Logarithmic barrier method with predictor-corrector
extensions. A powerful basis recovery (cross
over) algorithm combines the speed of the IPM
solution with the warm restart property of the
SSX.
- Mixed integer programs are solved by applying
a branch and bound tree search method. By incorporating
up to date cutting plane methods and integer
preprocessing techniques the MIP solver engine
is kept highly competitive and effective in
solving discrete optimisation problems. The
mixed integer programming feature can run under
a single or multiple distributed memory parallel
processors and performance can be tuned for
both these platforms.
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| Connected
|
| |
The
solver is connected to two of the optimisation industry's
leading modelling systems MPL and AMPL which ensures
rapid prototyping of powerful analyst and decision
support applications. The seamless connection is
also available with the OptiMax2000 callable library
and ensures that users can create powerful, customised
applications from within spreadsheets, Visual Basic,
or other RAD environments. See our Optimisation
Suites for more details. |
| Embeddable |
| |
FortMP is also available
as a callable library that makes it easy to carry
out optimisation based application development with
an embedded solver. The library is callable both
from C and from Fortran 90 user programs |
| Advantages |
| |
- Modular Design, finely tuned for Serial or
Parallel platforms.
- Can be embedded within other software environments.
- Available in object form as a callable library.
Source code can be made available.
- A range of applications can be constructed
by calling various sub-routines from a main
C or Fortran program.
|
| Platforms |
| |
- DOS, Win95/NT
- Most variants of UNIX and Linux
|
| |
|
FortMP
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