BlueM.Opt

BlueM.Opt | Usage | Development

Simulation-based optimization

Screenshot

Description

BlueM.Opt is an optimization framework that can be coupled with an arbitrary simulation software (only requirement: input data and results are to be stored in ASCII format). The optimization parameters, objective functions and (optionally) boundary conditions are defined in a flexible manner.

Optimization results are stored in a database.

BlueM.Opt integrates a graphing feature for displaying the optimization progress and results. Optimization results can also be analyzed in detail.

Where possible, BlueM.Opt utilizes multithreading in order to evaluate multiple parameter sets simultaneously.

List of available methods (optimization algorithms):

• PES: Parametric Evolution Strategy
• CES: Combinatorial Evolution Strategy
• HYBRID: Combination of PES and CES
• Hooke & Jeeves: Hillclimbing Algorithm
• MetaEvo: multicritera, hybrid optimization algorithm
• DDS: Dynamically Dimensioned Search

another method is

• SensiPlot: Sensitivity analysis (no optimization)
• Traveling Salesman

List of currently implemented simulation models:

• BlueM.Sim
• SMUSI
• S:CAN
• SWMM
• Test problems

Downloads

• BlueM.Opt Downloads

Application

• Instructions for the Application of BlueM.Opt (PDF-Export)
• Documentation of the input files
• Documentation of the output files

Development

• BlueM.Opt Development
  • Glossary
  • Documentation of the Codes
  • Bug tracking: Bugzilla
  • Compilation

Internal

• Documentation of the SVN Repository