Description: 旅行商问题动态规划算法的应用
某售货员要到若干城市去推销商品，已知各城市之间的路程（或旅费）。他要选定一条从驻地出发，经过每个城市一遍，最后回到驻地的路线，使总的路程（或旅费）最小。
-TSP dynamic programming algorithm of a salesman to a number of cities to sell commodities, known the distance between cities (or travel). He selected from a resident, after each city again, the last resident to return to the line, making the total distance (or travel) is the smallest. Platform: |
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Author:586 |
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Description: 旅行商问题动态规划算法的应用
某售货员要到若干城市去推销商品，已知各城市之间的路程（或旅费）。他要选定一条从驻地出发，经过每个城市一遍，最后回到驻地的路线，使总的路程（或旅费）最小。
-TSP dynamic programming algorithm of a salesman to a number of cities to sell commodities, known the distance between cities (or travel). He selected from a resident, after each city again, the last resident to return to the line, making the total distance (or travel) is the smallest. Platform: |
Size: 61440 |
Author:586 |
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Description: 旅行商问题_数组实现
请设计出一个动态规划算法
程序设计
任给一个输入实例，能输出最短路程及其路线
能用图形演示旅行商的推销路线-Traveling Salesman Problem _ array to achieve, please design a dynamic programming algorithm to a program design any input example, can output the shortest distance and routes can be used to sell graphical presentation of the traveling salesman route Platform: |
Size: 116736 |
Author:战天 |
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Description: 用动态规划算法求解旅行商销售员问题，给出一个耗费矩阵，能够得出最短路径长度和最短路径。-Using dynamic programming algorithm to solve traveling salesman salesman problem, given a cost matrix, able to draw the shortest path length and the shortest path. Platform: |
Size: 2043904 |
Author:wu |
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Description: 针对传统的算法如遗传算法、粒子群算法等在TSP问题上求解精确性和求解规模上都还有一定的不足，本文提出了一种基于动态规划思想的粒子群优化算法。该算法用动态规划的方法实现粒子间的信息交互和粒子的进化，并且将粒子群中的粒子按无标度信息指导网络拓扑图的方式进行连接。仿真结果表明该方法能有效地减小误差率，提高解的精确，同时还保持了较低的计算复杂度，具有良好的稳健性。-TSP problem solving for the traditional algorithms such as genetic algorithms, particle swarm optimization accuracy and solving the scale, there is a certain lack of a dynamic programming algorithm-based particle swarm optimization algorithm. The algorithm using dynamic programming method to achieve the evolution of information exchange between the particles and the particles, and particle swarm particle scale-free information guide network topology map to connect. The simulation results show that this method can effectively reduce the error rate and improve the solution precision, while maintaining a low computational complexity, good soundness. Platform: |
Size: 314368 |
Author:程徐 |
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Description: 基于蚁群算法的机器人的路径规划问题蚁群算法，一种与传统的数学规划原理截然不同的，模拟自然生态系统以求解复杂优化问题(如NPC(NP Complete)类问题，典型的有TSP(Traveling Saleman Problem)问题)的仿生优化算法，因其较强分布式计算机制、鲁棒性、易于与其他方法相结合等优点，使得蚁群算法具有较广泛应用领域，为那些最优化技术难以解决的组合优化问题提供了一类新的切实可行的解决方案。从最初的一维的静态优化问题扩展到多维的动态组合优化问题，包括车辆路径规划，工程设计，电力系统，图像处理，通讯系统，机器人系统，以及制造系统等领域。该文所研究的内容是其中之一——机器人的路径规划问题。
机器人路径规划是机器人学的一个重要研究领域，引起了众多研究者的关注。栅格法模型是众多环境建模方法中的一类实时性很强的路径规划模型。该文引入蚁群算法的基本思想，接着在基本蚁群算法上提出改进策略，并通过经典的旅行商问题验证改进蚁群算法的正确性，然后在改进的蚁群算法的基础上使用栅格法的路径规划策略, 并编制相应程序进行验证。
-Ant colony optimization, a mathematical programming with the traditional principle distinct simulate natural ecosystems to solve complex optimization problems (such as the NPC (NP Complete) class of problems, typically a TSP (Traveling Saleman Problem) problem) bionic optimization algorithm , because of its strong distributed computer system, robustness, ease combined with other methods, etc., makes the ant colony algorithm has a wider application areas, for those most difficult to solve optimization combinatorial optimization problems provide a new class of practical solutions. From the initial one-dimensional static optimization problem extended to multi-dimensional dynamic combinatorial optimization problems, including vehicle path planning, engineering design, power systems, image processing, communication systems, robotic systems, and manufacturing systems. In this paper, the contents of the study is one of these- robot path planning issues. Platform: |
Size: 1100800 |
Author:lin |
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Description: 全书包括两部分共15章。第1章指出问题求解困难的原因；第2章简要介绍几本概念；第3-5章分别综述穷举搜索法、局部搜索法、贪婪法、分而治之法、动态规划法、分支定界法、模拟退火法和禁忌搜索法；第6-7章介绍一般演化算法的细节问题；第8-10章介绍如何采用演化方法求解TSP问题、处理约束条件以及算法调整；第11章讨论了环境和噪声问题；第12-13分别提供神经网络和模糊系统相关内容；第14章对混合系统和扩展演化算法做简短讨论；第15章介绍演化算法在实际问题中的应用，并给出有价值的提示。-The book includes two parts with 15 chapters. The first chapter points out the reasons for the problem solving difficult the second chapter briefly introduces some of the concepts Chapter 3-5 respectively in exhaustive search, local search, greedy, divide and rule method, dynamic programming, branch and bound method, simulated annealing and tabu search method 6-7 chapter details the general evolution algorithm how to 8-10 chapter introduces evolution method for solving TSP problem, constraint conditions and algorithm the eleventh chapter discusses the environment and the problem of noise the 12-13 respectively with neural network and fuzzy system related content the fourteenth chapter on the mixing system and evolution algorithm is briefly discussed the fifteenth chapter introduces the application of evolutionary algorithm in practical problems, and gives valuable hints. Platform: |
Size: 10104832 |
Author:alvin |
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Description: 旅行商问题，用的是动态规划算法，需要自己输入结点和弧长，例如A B 3，表示A B 之间的弧长距离为3-Traveling salesman problem, using a dynamic programming algorithm, you need to enter your node and arc length, for example, AB 3, showing the arc between three distances AB Platform: |
Size: 2048 |
Author:刘丽 |
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Description: 这是一个关于著名最短路问题 旅行商问题的C++实现，本代码里面包含了两种实现方法：（1）动态规划求解TSP （2）蚁群算法求解TSP-This code is programed in C++ to solve TSP problem, which include two algorithm:（1）dynamic programming and (2)ant colony optimization Platform: |
Size: 3072 |
Author:chen |
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Search - TSP dynamic programming algorithm