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Search - particle swarm for tsp source code

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[CSharp] VRP

Description: 经典的粒子群算法（PSO），通过迭代搜索更新产生更优良的下一代解。供大家参考学习-classical PSO (PSO), through iterative search update produce the next generation better solution. For your reference learning
Platform: | Size: 24576 | Author: 笑容 | Hits:

[AI-NN-PR] tsp

Description: 这是一个很好用的求解TSP问题的粒子群算法，很适合初学者。-This is a very good solution of TSP used in the particle swarm optimization problems, it is suitable for beginners.
Platform: | Size: 2048 | Author: zhaogang | Hits:

[AI-NN-PR] GPSOtsp

Description: 采用遗传微粒群算法（GPSO）求解旅行商问题（TSP）的源代码。内附多个算例，本算法对于中小规模问题求解效率很高，对于大规模问题则效率略低。如有任何疑问，请于http://2shi.phphubei.com.cn/index.php发帖询问。-Genetic Particle Swarm Optimization (GPSO) for Traveling Salesman Problem (TSP) of the source code. Containing a number of examples, the algorithm for solving small and medium-sized high efficiency, large-scale problems for the slightly lower efficiency. If you have any questions, please post http://2shi.phphubei.com.cn/index.php asked.
Platform: | Size: 936960 | Author: 李剑 | Hits:

[Bio-Recognize] PSOTSPMatlabProgram

Description: 粒子群算法求解TSP问题Matlab源代码-Particle swarm optimization algorithm for TSP problem Matlab source code
Platform: | Size: 4096 | Author: ph | Hits:

[AI-NN-PR] tsp_pso

Description: tsp 粒子群算法修正源码， 参考：大连理工大学 谷超 2009年硕士学位论文 “改进的ACO和PSO算法在TSP中的应用” 　　 *郭文忠1，陈国龙1，洪玉玲2 .求解TSP问题的动态邻域粒子群优化算法.漳州师范学院学报(自然科学版) -modified particle swarm optimization tsp source code, reference: Dalian University of Technology master s degree thesis Valley over 2009, " Improved ACO and PSO algorithm for TSP application in the" * Guo Wenzhong 1, CHEN Guo 1, Hong Yuling 2. to solve the problem of dynamic neighborhood TSP PSO domain. Zhangzhou Teachers College (Natural Science)
Platform: | Size: 21504 | Author: ven | Hits:

[Windows Develop] PGPSOtspa

Description: 采用遗传微粒群算法（GPSO）求解旅行商问题（TSP）的源代码。内附多个算例，本算法对于中小规模问题求解效率很高，对于大大规模问题则效率略低。如有任何疑问。 -Genetic particle swarm optimization (GPSO) for solving the traveling salesman problem (TSP) source code. Included several examples of this algorithm for small and medium scale problem solving efficiency is very high, slightly lower efficiency for large massive problem. If you have any questions.
Platform: | Size: 937984 | Author: ackchengg | Hits:

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