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Simulation-based optimization
Scatterplot Matrix


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) 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

List of currently implemented applications (simulation models):




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




  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., 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,
  3. 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