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OPTIMISE: An Internet-Based Platform for Metamodel-Assisted Simulation Optimization

  • Amos Ng
  • Henrik Grimm
  • Thomas Lezama
  • Anna Persson
  • Marcus Andersson
  • Mats Jägstam
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 4)

Computer simulation has been described as the most effective tool for de-signing and analyzing systems in general and discrete-event systems (e.g., production or logistic systems) in particular (De Vin et al. 2004). Historically, the main disadvantage of simulation is that it was not a real optimization tool. Recently, research efforts have been focused on integrating metaheuristic algorithms, such as genetic algorithms (GA) with simulation software so that “optimal” or close to optimal solutions can be found automatically. An optimal solution here means the setting of a set of controllable design variables (also known as decision variables) that can minimize or maximize an objective function. This approach is called simulation optimization or simulation-based optimization (SBO), which is perhaps the most important new simulation technology in the last few years (Law and McComas 2002). In contrast to other optimization problems, it is assumed that the objective function in an SBO problem cannot be evaluated analytically but have to be estimated through deterministic/ stochastic simulation.

Keywords

Pareto Front Winter Simulation Slave Processor Metamodeling Method Optimal Computing Budget Allocation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Amos Ng
    • 1
  • Henrik Grimm
    • 1
  • Thomas Lezama
    • 1
  • Anna Persson
    • 1
  • Marcus Andersson
    • 1
  • Mats Jägstam
    • 1
  1. 1.Centre for Intelligent AutomationUniversity of SkövdeSweden

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