The Researching And Application Of PSO

In the problem of allocating resources, optimization means to meet the constraints of how to allocate resources needed to make the system cost the least, access to the most economic benefits.In this paper economic dispatch problem is a typical class, according to the number of different optimization objectives.The problem can be divided into two types composed of single objective and multi-objective economic dispatch problem.Chaos has the initial value sensitivity, randomness, ergodicity and other characteristics. As a new research method, it has been successfully combined with a variety of algorithms with its excellent characteristics in this paper. This combination is mainly the use of the ergodic chaotic, randomly search a better performance within the state. Different searching metholds have different possibility to find the better performance. This paper improves a Tent mapping to make the chaotic sequence is more uniform. Then, a new chaotic searching of linear decreasing the radius , by comparing the experimental results show the new way has higher efficient than traditional carrier .As a heuristic, Particle swarm optimization algorithm is a kind of intelligent algorithms simulated the social behavior of bird or fish. As an optimization tool, PSO has been widely applied to the single-objective and multi-objective optimization problem. In the multi-objective optimization process, Traditional particle swarm is easily to have the phenomenon of "stagnation" during the later stage of evolution.In the same time, Population may fall into local optimum.Also In the multi-objective optimization process, Population may fall into local optimum too.The paper come over the bugs over through integration of the new chaotic search method. In addition, in multi-objective optimization process, using of local chaotic search method can also enhance the diversity and convergence of solutions in this process.Finally, Applicating to the single-objective of economic dispatch and multi-objective economic dispatch problem to illustrate the improved algorithm has higher efficiency. In solving the single-objective of economic dispatch, the solution obtained by the improved algorithm consumed less total energy. In solving the single-objective of economic dispatch, the improved algorithm considered focused on energy consumption and pollution emission, the solution obtained by the improved algorithm has less polluting emissions when consumpted the same energy.