粒子群算法在離散優(yōu)化問題中的研究.pdf

1、廣西師范大學碩士學位論文粒子群算法在離散優(yōu)化問題中的研究姓名：熊磊申請學位級別：碩士專業(yè)：計算機軟件與理論指導教師：王強20060401Study of Study of Particle Swarm Optimization Particle Swarm Optimizationin in Discrete iscrete Optimization ptimization Problem roblemAuthor：Lei Xiong；

2、 tutor：Qiang Wang； specialty：Computer Software & Theory；Research direction：Database System； Grade：2003Optimization is an important branch of mathematics and a young subject which is extensively used, andit aims at ch

3、oosing the optimum one from many candidate schemes to solve a practical problem. Manyscientific, engineering and economic problems need the optimization of a set of parameters with the aim ofminimizing or maximizing the

4、objective function. For example, how to choose the parameter in theengineering design can make the design scheme satisfy the need and decrease the cost, and how to allocatethe limit resource can make the design scheme sa

5、tisfy the need and get better economic benefit. Optimizationexits in all kinds of fields of human activities.The application of optimization methods is very extensive, and it involves a lot of problems and theseproblems

6、have different characteristics. According to different principles, they can be divided into differentclasses. For example, according to the value type of the decision- making variable, they can be divided intotwo classes

7、, function optimization problem and combination optimization problem (namely, discreteoptimization problem). The discrete optimization problem is an important optimization problem, and with thedevelopment of computer sci

8、ence, the science of the management and the technology of the modernizedproduce, it is getting more and more attention by the subjects of operational research, applicationsmathematics, computer science and management sci

9、ence. Since many years, people are trying to look forefficient algorithms to solve the combination problem, and many efficient algorithms have been proposed,but NP problem is still a science difficulty problem in the 21c

10、entury, and it is not solved in the complexityfield of the theory informatics yet.Modern optimization methods such as artificial neural network, tabu search, genetic algorithm and antcolony algorithm etc., have shown cap

11、abilities of finding optimal solutions to many real- word complexproblems within a reasonable amount of time. These methods have forged close ties with neural science,artificial intelligence, statistical mechanics, and b

12、iology evolution etc., some of them are called intelligentoptimization algorithms, such as genetic algorithm and ant colony algorithm.Recently, particle swarm optimization (PSO) algorithm has been gradually attracted mor

13、e attention overanother intelligent algorithm .PSO was brought forward by Dr. Eberhart and Dr. Kenney in 1995. It was apopulation based stochastic method motivated by the social behavior of bird flock. PSO shares manysim