Scroll Plate Optimization Based on Improved Genetic-Particle Swarm Optimization Algorithm

Abstract

The part optimization is very important for scroll compressor design. According to existing problems of current optimization algorithm and actual optimization problems, the improved genetic-particle swarm optimization algorithm (IGA-PSO) is proposed for scroll plate optimization. The optimization method integrates crossover of genetic algorithm (GA) and evolutionary mechanism of particle swarm optimization (PSO), the main structure parameters are been as control variable, the optimization mathematics model is developed, making use of crossover of GA and evolutionary mechanism of PSO, IGA-PSO realizes the purpose of minimizing the value of objective function. IGA-PSO is applied to scroll plate optimization on computer, it is shown that the improved approach converges to better solution much faster than the earlier reported approaches through compared with other methods and tested of prototype performance. All the results supply theory and technology support for wide application of PSO in engineering