Optimization of High Pressure Common Rail Electro-injector Using Genetic Algorithms
The aim of the present investigation is the implementation of an innovative procedure to optimise the design of a high pressure common rail electro-injector. The optimization method is based on the use of genetic programming, a search procedure developed by John Holland at the University of Michigan. A genetic algorithm (GA) creates a random population which evolves combining the genetic code of the most capable individual of the previous generation. For the present investigation an algorithm which includes the operators of crossover, mutation and elitist reproduction has been developed. This genetic algorithm allows the optimization of both single and multicriteria problems. For the determination of the multi-objective fitness function, the concept of Pareto optimality has been implemented. The performance of the multiobjective genetic algorithm was examined by using appropriate mathematical functions and was compared with the single objective one.