Research Of Function Optimization Of PSO Based On Simulated Annealing

Abstract:In this paper, the the study particle swarm optimization algorithm and simulated annealing algorithm based on the fusion of two algorithms, clever use of two optimization algorithms for a little bit, to avoid the shortcomings of the two algorithms, create a new algorithm, this algorithm known asas based on simulated annealing particle swarm optimization algorithm, and elected by a plurality of standard optimization test function, using the proposed algorithm to optimize access to images and data analysis, whose main work:(1) The research of The first two algorithms, particle swarm algorithms and simulated annealing algorithm, carry out a full range of research, including the principle of the algorithm, thoughts, processes, and its programming using MATLAB to study its performance.(2)The creation of the algorithm. The successful integration of the advantages of using particle swarm algorithm and simulated annealing algorithm, the proposed algorithm, later described the proposed algorithm, including:algorithm principle, the steps of the algorithm, the algorithm flowchart using MATLAB.(3)The research of test function. Test function to optimize the selection of the six kinds of standard test functions, given the optimal values of the six test functions, and use MATLAB to draw out its surface chart.(4) Testing the algorithm. Using this algorithm optimization test function selected a wide range of tests, including:test curve, optimizing the position of the particle before and after contrast,50independent experiments.(5) The test-data analysis. Analysis of the data generated by the test, indicating the availability of the algorithm, the convergence of the validity and superiority.(6) We slove FSP problem Using simulated annealing particle swarm optimization, test typical problems Car and REC Questions, and compared to other algorithms for solving data analysis。...