Abstract
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.
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Note that this assumption may not be valid in certain circumstances where counter-gradient transport may occur.
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© 2011 Springer-Verlag London Limited
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Shi, Y., Ge, HW., Reitz, R.D. (2011). Fundamentals. In: Computational Optimization of Internal Combustion Engines. Springer, London. https://doi.org/10.1007/978-0-85729-619-1_2
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DOI: https://doi.org/10.1007/978-0-85729-619-1_2
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Online ISBN: 978-0-85729-619-1
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