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Multikriterielle Evolutionsstrategie der [http://www.ihwb.tu-darmstadt.de/mitarbeiter/dirk.muschalla/PromotionMuschalladigital.pdf Promotion] von Dirk Muschalla. Die Programmierung besteht aus einem allgemeingültigen Tool, dass aus einer Dynamic Link Library und zwei Steuerelementen zur Einbindung mit Visual Basic programmierten GUIs besteht. Die DLL enthält die eigentlichen Funktionen und Methoden der ES. Das ansprechen der ES und die Verbindung mit unterschiedlichen Simulationsprogrammen muss für die jeweilige Problemstellung angepasst werden.
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{{BlueM.Opt_nav}}
[[File:Simulation-based-optimization.png|thumb|Simulation-based optimization]]
[[File:EVO Box screenshot.png|thumb|Screenshot]]
[[File:Scatterplot screenshot.png|thumb|Scatterplot Matrix]]
==Description==
BlueM.Opt is an optimization framework that can be coupled with an arbitrary simulation software (only current requirement: input data and results are to be stored in ASCII format). The optimization parameters, objective functions and (optionally) contraints can be defined in a flexible manner.


==Anwendung==
Optimization results are stored in a [[BlueM.Opt output files|database]].  
* Dokumentation der [[EVO.NET Eingabedateien | Eingabedateien]]
* Dokumentation der [[EVO.NET Ausgabedateien | Ausgabedateien]]
* Hinweise zur [[EVO.NET Benutzung | Benutzung]]
* ([[EVO.NET Doku Export |Seite zum Exportieren der Dokumentation]])


==Entwicklung==
BlueM.Opt integrates a graphing feature for displaying the optimization progress and results. Optimization results can also be analyzed in detail.
* Dokumentation der [[EVO.NET SVN | SVN Repository]] (http://130.83.196.170/ihwbsvn/EVO.NET)
* Dokumentation des [[EVO.NET Code | Codes]]
* Aktuelle [[EVO.NET To Do | To Do Liste]]
* Hinweise zur [[EVO.NET Kompilierung | Kompilierung]]


[[Kategorie:EVO]]
Where possible, BlueM.Opt utilizes multithreading in order to evaluate multiple parameter sets simultaneously.
 
List of currently implemented applications (simulation models):
* '''[[BlueM.Sim]]'''
* '''[[TALSIM|Talsim-NG]]'''
* '''<del>[[SMUSI]]</del>''' (''currently not included [https://github.com/bluemodel/BlueM.Opt/issues/184 #184]'')
* '''[[SWMM]]'''
* '''[[Test problems]]'''
* '''[[Traveling Salesman]]'''
 
List of available methods (optimization algorithms):
* '''[[PES]]''': Parametric Evolution Strategy
* '''[[Hooke & Jeeves]]''': Hillclimbing Algorithm
* '''[[MetaEvo]]''': multicritera, hybrid optimization algorithm
* '''[[DDS]]''': Dynamically Dimensioned Search
other included methods are
* '''[[SensiPlot]]''': Sensitivity analysis (no optimization)
* '''[[TSP]]''' (only for [[Traveling Salesman]])
 
==Downloads==
Download BlueM.Opt from GitHub: https://github.com/bluemodel/BlueM.Opt/releases/latest
 
==Usage==
* '''[[BlueM.Opt Usage]]'''
** Documentation of the [[BlueM.Opt input files| input files]]
** Documentation of the [[BlueM.Opt output files| output files]]
 
==Literature==
* {{:Literatur:Muschalla 2006}}
* {{:Literatur:Muschalla 2008}}
* {{:Literatur:Muschalla et al. 2009}}
* {{:Literatur:Kerber_2009}}
* {{:Literatur:Froehlich & Hübner 2009}}
 
==Development==
* [[BlueM.Opt Development]]
** [[BlueM.Opt Begriffsklärung | Glossary]]
** Documentation of the [[BlueM.Opt Code|code]]
 
==Literature==
<references/>
 
[[Category:BlueM.Opt]]

Latest revision as of 10:33, 11 February 2024

EVO.png BlueM.Opt | Download | Usage | Development

Simulation-based optimization
Screenshot
Scatterplot Matrix

Description

BlueM.Opt is an optimization framework that can be coupled with an arbitrary simulation software (only current requirement: input data and results are to be stored in ASCII format). The optimization parameters, objective functions and (optionally) contraints can be 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 currently implemented applications (simulation models):

List of available methods (optimization algorithms):

  • PES: Parametric Evolution Strategy
  • Hooke & Jeeves: Hillclimbing Algorithm
  • MetaEvo: multicritera, hybrid optimization algorithm
  • DDS: Dynamically Dimensioned Search

other included methods are

Downloads

Download BlueM.Opt from GitHub: https://github.com/bluemodel/BlueM.Opt/releases/latest

Usage

Literature

  • Muschalla (2006)[1]
  • Muschalla (2008)[2]
  • Muschalla et al. (2009)[3]
  • Kerber (2009)[4]
  • Froehlich & Hübner (2009)[5]

Development

Literature

  1. Muschalla, Dirk (2006): Evolutionäre multikriterielle Optimierung komplexer wasserwirtschaftlicher Systeme. PhD thesis, Vol. 137/2006, Technische Universität Darmstadt, Mitteilungen des Instituts für Wasserbau und Wasserwirtschaft, Fachgebiet für Ingenieurhydrologie und Wasserbewirtschaftung.
  2. Muschalla, D. (2008): Optimization of integrated urban wastewater systems using multi-objective evolution strategies, Urban Water Journal, 5:1, 59-67, doi:10.1080/15730620701726309
  3. Muschalla, D., Froehlich, F., Heusch, S., Hübner, C., Kerber, D., Reußner, F. and Ostrowski, M. (2009): BlueM.Opt - a generic framework for simulation based optimization information.png - International Stormwater and Urban Water Systems Modeling Conference, Toronto, Canada, February 19, 2009,
  4. Kerber, D. (2009): Entwicklung eines multi-kriteriellen, hybriden Optimierungsalgorithmus für den Einsatz in der Kanalnetzsteuerung information.png, Diplomarbeit, TU Darmstadt
  5. Froehlich, F. & Hübner, C. (2009): Kopplung von Simulation und Optimierung - Eine Vorstellung von BlueM.Opt information.png, 1. Darmstädter Ingenieurkongress - Bau und Umwelt, 14.-15.09.2009, Darmstadt