• Yu Shi
  • Hai-Wen Ge
  • Rolf D. Reitz


In  Chap. 1, a survey was conducted of recent computational optimization studies of engine design using various methods. Most of these optimization algorithms can be categorized into two classes, i.e., gradient-based methods and gradient-free methods, or specifically, evolutionary methods.

This section explores the advantages and limitations of these optimization algorithms with three mathematical problems. The commercial software modeFRONTIER (ESTECO, 2008) was used to compare different optimization algorithms with model problems. The theoretical fundamentals of three multi-objective genetic algorithms (MOGA) are discussed in detail, while the assessment of these three MOGAs in computational engine optimization is the subject of  Chap. 4.


Large Eddy Simulation Pareto Front Mixture Fraction Premix Flame Conditional Moment Closure 
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.

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Department of Chemical EngineeringMassachusetts Institute of TechnologyCambridgeUSA
  2. 2.Engine Research CenterUniversity of WisconsinMadisonUSA

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