Difference between revisions of "Category:Optimization"
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For PlanWise an optimization tool has been developed for formulating and solving LP and MIP problems. It is basically a graphical user interface to the [http://zimpl.zib.de/ ZIMPL optimization modelling language]. For solving a problem, external third-party solvers are used and directly linked to the optimization tool. Currently, the solvers available are | For PlanWise an optimization tool has been developed for formulating and solving LP and MIP problems. It is basically a graphical user interface to the [http://zimpl.zib.de/ ZIMPL optimization modelling language]. For solving a problem, external third-party solvers are used and directly linked to the optimization tool. Currently, the solvers available are | ||
| − | *[http://lpsolve.sourceforge.net/ LPSolve], which is freely available, and | + | *[http://lpsolve.sourceforge.net/ LPSolve], which is freely available, |
| − | *[http://www.ilog.com/products/optimization/archive.cfm?acc=ggopt&gp=cplex&source=cpc&cmpn=cplex ILOG CPLEX], which is a very efficient, state-of-the-art solver. | + | *[http://scip.zib.de SCIP/Soplex], which is freely available for academic use, and |
| + | *[http://www.ilog.com/products/optimization/archive.cfm?acc=ggopt&gp=cplex&source=cpc&cmpn=cplex ILOG CPLEX], which is a very efficient, state-of-the-art solver. It requires that the user has a licence, which can be obtained for free for academic use. | ||
The optimization model is linked to a Heureka-formatted SQL Server database used for storing input data, simulation data, and result data. This enables a seamless integration with the input data required by the optimization model, as well as direct presentation of optimization results in the form of tables, graphs, and maps. This simplifies the analysis and visualization of scenarios or plans of forest development and outputs. | The optimization model is linked to a Heureka-formatted SQL Server database used for storing input data, simulation data, and result data. This enables a seamless integration with the input data required by the optimization model, as well as direct presentation of optimization results in the form of tables, graphs, and maps. This simplifies the analysis and visualization of scenarios or plans of forest development and outputs. | ||
Revision as of 11:56, 20 May 2011
About the optimization tool
For PlanWise an optimization tool has been developed for formulating and solving LP and MIP problems. It is basically a graphical user interface to the ZIMPL optimization modelling language. For solving a problem, external third-party solvers are used and directly linked to the optimization tool. Currently, the solvers available are
- LPSolve, which is freely available,
- SCIP/Soplex, which is freely available for academic use, and
- ILOG CPLEX, which is a very efficient, state-of-the-art solver. It requires that the user has a licence, which can be obtained for free for academic use.
The optimization model is linked to a Heureka-formatted SQL Server database used for storing input data, simulation data, and result data. This enables a seamless integration with the input data required by the optimization model, as well as direct presentation of optimization results in the form of tables, graphs, and maps. This simplifies the analysis and visualization of scenarios or plans of forest development and outputs.
As an alternative to the integrated optimization tool, an AIMMS model has been developed, which may be more suitable for a OR researcher or the very advanced user who needs maximum flexibility or maximum optimization performance. This model is also linked to the same database, but is run as a separate application. It also requires an AIMMS licence.
A number of basic models will be developed with the built-in optimization tool. A user should be able to use these as they are, or as a starting point for further development.
User's guide
Optimization models developed or under development
Non-spatial model for analyzing sustainable cut and other values (available)
Harvest scheduling with clustering of old growth areas and harvest areas
Harvest scheduling including road access, AAC constraints, opening size constraints, and harvest flow constraints
Other options
Ongoing research
We have had the pleasure of hosting a finnish postdoc during 2007-2008, dr Tero Heinonen. He has developed a software application in which optimization algorithms are combined with cellular automata to solve spatial problems when raster cells are used as description units instead of stands. The application can read from the Heureka database directly and could become available in the future.