《基于一种混合智能优化算法的TSP求解》-毕业学术论文（设计）.doc

PAGE l PAGE \* MERGEFORMAT1 基于一种混合智能优化算法的TSP求解 摘要：粒子群算法（PSO）是一种基于群体迭代，利用群体在解空间中追随最优粒子进行有哪些信誉好的足球投注网站的计算智能方法，PSO的优点在于收敛速度快、设置参数少，简单易实现。遗传算法（Genetic Algorithm）是一种借鉴生物界自然选择和自然遗传机制的随机化有哪些信誉好的足球投注网站算法，具有内在的隐并行性和更好的全局寻优能力。旅行商（TSP）问题，是图论中有代表性的组合优化问题，已被证明具有NPC计算复杂性。本文主要结合粒子群算法和遗传算法，重点研究分析了基于上述两种算法的智能混合算法寻优，并将它应用到TSP问题的求解上。程序仿真结果表明，该智能混合优化算法既克服了粒子群算法无法跳出局部最优解的缺点，又解决了遗传算法后期收敛速度慢的缺点。 关键词：粒子群算法，遗传算法, TSP，混合优化算法 Based on a Hybrid Intelligent Optimization Algorithm for Solving TSP Abstract：Particle swarm optimization algorithm is an algorithm bases on group iteration and uses groups to search the optimal particle in the space of solution.The advantages of PSO are many, such as faster calculation speed,less parameters and easy to implement.Genetic algorithm is a random search algorithm which is the simulation of the biological natural selection and the natural genetic mechanism. The characters of genetic algorithm are many too, such as implicit parallelism and better ability of global searching .Traveling salesman problem is a representative combination optimization problemand has proved to beNPC computational complexity problem. This paper mainly combines the particle swarm algorithm andgenetic algorithmto research and analyze the intelligent hybrid algorithm which bases on the above two algorithms, and the intelligent hybrid algorithm be used to solve TSP. Due to the particle swarm algorithm’s disadvantage is cannot out of local optimal solutionand the genetic algorithm’s problemis the slow convergence speed in later stage so theintelligent hybrid algorithmcan be used to solve those problems.. Keywords:TSP, Particle swarm algorithm, Genetic algorithm,Hybridoptimization algorithm. 目录 TOC \o 1-3 \h \z \u HYPERLINK \l _Toc324675366 1.引言 PAGEREF _Toc324675366 \h 2 HYPERLINK \l _Toc324675367 1.1研究背景和课题意义 PAGEREF _Toc324675367 \h 2 HYPERLINK \l _Toc324675368 1.2智能优化研究现状 PAGEREF _Toc324675368 \h 3 HYPERLINK \l _Toc324675369 1.3本文主要内容 PAGEREF _Toc324675369 \h 4 HYPERLINK \l _Toc324675370 2.T