求解tsp问题的局部优化算法

基于感知器神经网络处理复杂的分类问题-based perceptron neural network to handle complex classification problems

TSP双种群蚁群算法。还包括了“30城市TSP问题数据与最优解.mat”，“75城市TSP问题数据.mat”，和“442TSP问题数据与算法对比.mat”-TSP-Stocks ant colony algorithm. Also include "30 cities TSP data and the optimal solution. Mat, " "75 cities TSP data. mat, " and "442TSP problem with the algorithm for data comparison. mat "

神经网络C程序的第8章-neural network C procedures for the Chapter 8

L-M算法。除了动量法(基于梯度下降的训练算法)外，学习率自适应调整策略是BP算法改进的另一种途径，它利用Levenberg-Marquardt优化方法，从而使得学习时间更短。其缺点是，对于复杂的问题，该方法需要很大的存储空间。 -L-M algorithm. In addition to momentum (based on the gradient descent algorithm for training), learning rate adaptive strategy is to improve the algorithm BP Another approach, which uses Levenberg-Marquardt optimization method, which makes learning time is even shorter. Its weakness is that the complex problems that the method requires a lot of storage space.

是MATLAB的RBF神经网络建模程序，比较有参考价值阿，需要的就下吧-MATLAB is the RBF neural network modeling procedures, more A reference value, we need it on the next

本程序用模拟退火算法实现了旅行商问题（tsp问题）-the procedures used simulated annealing algorithm to achieve the traveling salesman problem (tsp)

美国麻省理工学院出的遗传算法方面的好书.-Massachusetts Institute of Technology in the United States out of aspects of genetic algorithms books.

这是一个用MATLAB软件写的遗传算法程序。-This is a software written using MATLAB genetic algorithm procedure.

bp神经网络 c语言程序-bp neural network c Language Program

4。《演化程序――遗传算法和数据编码的结合》，[英]米凯利维兹着 科学出版社 2000年第一版 本书分三个部分共16章分别介绍了:1.遗传算法的概念、数学原理及方法步骤 2.遗传算法和数据编码联系起来所构成的演化程序 3.演化程序面向一些实际问题的应用。 本书语言生动，结构合理，较少使用专业性术语和深涩词汇，适合面临优化问题的研究生、程序员、设计师、工程师及科研工作人员参考。-4. "Evolutionary process-- genetic coding algorithm and data integration," [E] Mikhail Liweici a 520-531 2000 version of the first book in three parts a total of 16 chapters were introduced : 1. Genetic Algorithm concept mathematical principles and methods of Step 2. genetic algorithms and data coding linked posed by the evolution of procedures 3. Evolution-oriented procedures some of the practical problems of application. The book vivid language, reasonable structure, and less use of professional terminology and vocabulary deep acerbic suitable for optimization problems facing graduate students, programmers, designers, engineers and research personnel.