A hybrid method of modified NSGA-II and TOPSIS to optimize performance and emissions of a diesel engine using biodiesel
作者： Mir Majid Etghani , Mohammad Hassan Shojaeefard , Abolfazl Khalkhali , Mostafa Akbari
DOI: 10.1016/J.APPLTHERMALENG.2013.05.041
关键词:
摘要: Abstract This paper addresses artificial neural network (ANN) modeling followed by multi-objective optimization process to determine optimum biodiesel blends and speed ranges of a diesel engine fueled with castor oil (COB) blends. First, an ANN model was developed based on standard back-propagation algorithm predict brake power, specific fuel consumption (BSFC) the emissions engine. In this way, multi-layer perception (MLP) used for non-linear mapping between input output parameters. Second, modified NSGA-II incorporating diversity preserving mechanism called e-elimination process. Six objectives, maximization power minimization BSFC, PM, NOx, CO CO2 were simultaneously considered in step. Optimization procedure resulted creating non-dominated optimal points which gave insight best operating conditions Third, approach TOPSIS method finding compromise solution from obtained set Pareto solutions.
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