SYSTEM OPTIMIZATION OF TURBOFAN ENGINES USING GENETIC ALGORITHMS

This paper presents an application of genetic algorithms to the system optimization of turbofan engines. Genetic algorithms are relatively n ew general-purpose optimization algorithms that apply the rules of nat ural genetics to explore a given search space. In order to characteriz e the many measures of aircraft engine performance, two different crit eria are chosen for evaluation. These criteria are thrust per unit mas s flow rate and overall efficiency. These criteria are optimized using four key parameters including Mach number, compressor pressure ratio, fan pressure ratio, and bypass ratio. After observing how each parame ter influences objective functions independently, the two objective fu nctions are combined to examine their interaction in a multiobjective function optimization. Numerical results indicate that genetic algorit hms are capable of optimizing a complex system quickly. The resultant parameter values agree well with previous studies.