Multi-objective Pareto optimization of axial compressors using genetic algorithms
Abstract
Multi-objective genetic algorithm (GAs) (non-dominated sorting genetic algorithm, NSGA-II) with a new diversity preserving mechanism is used for Pareto optimization of axial compressor. The conflicting design objectives of axial compressor are, total efficiency (ηtt), and pressure ratio (πs) and the input parameters are stage inlet angle (α1), inlet Mach number (M1), and the diffusion factor (D). Optimal Pareto front of the axial compressor is obtained which exhibit the trade-off between the corresponding conflicting objectives and, thus, provides different non-dominated optimal choices of axial compressors for designer.
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Stevens Point, Wisconsin, United States
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Published: 13 July 2006
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