Research On Evolutionary Optimization Algorithm And Its Application

Optimization is an age-old problem, could be solved by so many classical mathematical methods. With the development of science and technology, classical mathematical methods have been unable to meet the needs of technology, so evolutionary optimization algorithm appears at that moment. Evolutionary optimization algorithm is based on the bionics theory, which simulated the activities of individual animal to complete a series of operations.This paper describes the historical background and theoretical basis of optimization algorithm. It also introduces what the optimization and its related knowledge is. At the same time the particle swarm algorithm is applied to sensor networks and traffic lights controlling. The results are as follow:(1) This paper explains what optimization problem and its related knowledge is, describe the historical background and research situation at home and abroad of PSO.(2) This paper gives the algorithm theory and implementation steps of PSO GA and AFSA. Mathematical methods are used to describe the optimization problem, and set out the test function.(3) Linear system theory has been used in analyzing the reasons for PSO getting into local minimum. In order to jump out of local minimum to activate particles, this paper draws on the crowding factor of AFSA and proposes an improved PSO method based on feeding forward disturbance .When count the number of particles in the circle ,the current optimal value is the centre of the circle and the crowding factor is the radius. When the number is larger than one constant, it is considered to be trapped into local optimal value, so a disturbance is added to the system in advance. The simulation results have validated its effectiveness.(4) This paper attempts to analyze the structure of the three optimization algorithms by analyzing the serial algorithm and parallel algorithm and so on. Finally the similarities and differences between the three optimization algorithms and the algorithm used in different occasions. The choice of algorithms plays a guiding role. This combination of algorithms provides an effective theoretical basis.(5) Problem in the dynamic vision sensor networks is proposed firstly in this paper. The target is usually regarded as a centroid, Actually the target diameter may be larger than the sensor radius .Therefore the centroid modal is not suitable any more .To solve this problem, a direction adjustable vision sensing model is proposed, which is based on direction adjustable sensing model .Combined with this modal PSO, algorithm is also used to optimize the coverage probability. The simulation results have validated its effectiveness.(6) Solving the heavy traffic problem in existing condition is also worth considering. In this paper, the method of two-intersections traffic controlling is proposed. Using improved PSO, the time of green and red lights could be optimized to make the average wait time of vehicles shorter and the interferential phenomenon of cars in sections reduced. The simulation results show that it is an effective method...