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The Improvent And Applications Upon The Particle Swarm Optimization

Posted on:2008-08-05Degree:MasterType:Thesis
Country:ChinaCandidate:J J LiuFull Text:PDF
GTID:2178360242968383Subject:Applied Mathematics
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Particle swarm algorithm (PSO), which stems from the simulation of birds flock's looking for food, has been paid attention and researched wildly. PSO is easy to be understood ,PSO can be implemented easily because it hasn't many parameters to be adjusted, so it attracted attention of researchers in different fields quickly. It has become an important optimization implements and has been wildly applied to the object functions optimization, dynamic environments optimization, neural network training, and so on.Since it is a new method, some fundamental behavior is still not clear. In the application area, to combine it with local optimization algorithm, is still waiting for further study. In order to overcome some disadvantages of PSO such as easily trapped in the local optimum,easily to be premature, bad local search capability,This thesis put forward some revelant strategies according to the defects on the basis of the basic PSO. we apply the modified algorithm to the optimal design of thermal insulation on the pipeline. The main works are as follows:(1)In order to avoid being trapped in the local optimum, a new global optimum location mutation PSO algorithm and a new particle swarm optimization with dimension mutation operator are proposed.our work analyzed mutation time and mutation probability.(2)The paper puts forward a new Particle Swarm Optimization based on shrinking gene from the angle of information exchange manner. The new algorithm make particle utilize more available information of other particle. Moreover, it balances the contradiction between efficiency and precision of algorithm search by weight of individual best value and change action mode of particle.(3) Due to the lower local search ability and the lack of higher diversity of particles in PSO, a modified particle swarm optimization algorithm with crossover operator (MPSO)is presented to solve multidimensional constrained optimization problem. Also mutation operation which speeds up the local search is embedded to avoid the common defect of premature convergence and increases the diversity of population. (4)In order to solve PID parametr optimization problem, the global optimum location mutation PSO algorithm is applied to the PID controller tuning. The results are fairly well.In all, The paper makes an anaysis of PSO in detail. It not only puts forward several effective modified measures but also broads its application areas. Finally, the whole research contents were summarized, and further research directions were indicated.
Keywords/Search Tags:PSO, optimization, crossover operator, mutation operator
PDF Full Text Request
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