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Keywords

Function Evaluation Problem Instance Design Point Algorithm Design Performance Ratio 
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7.10 Further Reading

  1. Aggarwal, A. & Floudas, C. A. (1990). Synthesis of general distillation sequences—nonsharp separations. Computers & Chemical Engineering, 14, 631–653.CrossRefGoogle Scholar
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  5. Bartz-Beielstein, T. & Naujoks, B. (2004). Tuning Multicriteria Evolutionary Algorithms for Airfoil Design Optimization. Interner Bericht des Sonderforschungsbereichs 531 Computational Intelligence CI-159/04, Universität Dortmund, Germany.Google Scholar
  6. Bartz-Beielstein, T., Schmitt, K., Mehnen, J., Naujoks, B., & Zibold, D. (2004c). KEA—A Software Package for Development, Analysis, and Application of Multiple Objective Evolutionary Algorithms. Interner Bericht des Sonderforschungsbereichs 531 Computational Intelligence CI-185/04, Universität Dortmund, Germany.Google Scholar
  7. Bartz-Beielstein, T., Lasarczyk, C., & Preuß, M. (2005b). Sequential parameter optimization. In B. McKay & others (Eds.), Proceedings 2005 Congress on Evolutionary Computation (CEC’05), Edinburgh, Scotland, volume 1 (pp. 773–780). Piscataway NJ: IEEE Press.Google Scholar
  8. Bartz-Beielstein, T., Preuß, M., & Markon, S. (2005c). Validation and optimization of an elevator simulation model with modern search heuristics. In T. Ibaraki, K. Nonobe, & M. Yagiura (Eds.), Metaheuristics: Progress as Real Problem Solvers, Operations Research/Computer Science Interfaces (pp. 109–128). Berlin, Heidelberg, New York: Springer.Google Scholar
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  17. Mehnen, J., Michelitsch, T., Bartz-Beielstein, T., & Henkenjohann, N. (2004a). Systematic analyses of multi-objective evolutionary algorithms applied to real-world problems using statistical design of experiments. In R. Teti (Ed.), Proceedings Fourth International Seminar Intelligent Computation in Manufacturing Engineering (CIRP ICME’04), volume 4 (pp. 171–178). Naples, Italy.Google Scholar
  18. Mehnen, J., Michelitsch, T., Bartz-Beielstein, T., & Schmitt, K. (2004b). Evolutionary optimization of mould temperature control strategies: Encoding and solving the multiobjective problem with standard evolution strategy and kit for evolutionary algorithms. Journal of Engineering Manufacture (JEM), 218 (B6), 657–665.Google Scholar
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  23. Weinert, K., Mehnen, J., Michelitsch, T., Schmitt, K., & Bartz-Beielstein, T. (2004). A multiobjective approach to optimize temperature control systems of moulding tools. Production Engineering Research and Development, Annals of the German Academic Society for Production Engineering, XI(1), 77–80.Google Scholar

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