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Description: 在linux下C写的最大最小蚁群算法，用于解决VRP、TSP问题，效果发很好。-A MAX-MIN Ant System (MMAS) implemented in the Hyper-Cube Framework for the application to Unconstrained Binary Quadratic Programming (UBQP).
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Size: 318464 |
Author: mlon |
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Description: 使用C#算法解决30个城市的旅行商问题（TSP），程序代码内有详细的说明，适合C#语言的入门学习。-Using C# algorithm to solve the traveling salesman problem in 30 cities (TSP), the program code with detailed instructions for the C# language learning portal.
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Size: 4096 |
Author: 刘育成 |
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Description: 求解TSP问题的Hopfield网络设计。在一个城市集合{A,B,C,D}中找出一个最短且经过每个城市各一次并且回到起点的路径。-TSP problem Hopfield network design. In a city the set {A, B, C, D} in finding a shortest and after each city once and returned to the starting point of each route.
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Size: 1024 |
Author: 黄渭 |
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Description: 本研究开发一种混合自动进化模糊学习算法
决定了最优路径旅行附近大规模旅行商问题
(LSTSPs)。LSTSPs识别解决方案是一种最复杂的主题
全球的组合优化问题。提出的混合进化模糊
学习计划的优点结合自适应模糊c均值(FCM),简单
不等式性质合并的概念,模拟退火(SA)算法和一种有效的学习
表transform-based粒子群优化(TPSO)。本研究使用
方法来处理大型TSP路由系统。
应用进化TPSO学习算法-This study develops a hybrid evolutionary fuzzy learning algorithm that automatically
determines the near optimal traveling path in large-scale traveling salesman problems
(LSTSPs). Identifying solutions for LSTSPs is one of the most complicated topics in the field
of global combinatorial optimization problems. The proposed hybrid evolutionary fuzzy
learning scheme combines the advantages of the adaptive fuzzy C-means (FCM), simple
MAX–MIN merging concept, simulated annealing (SA) learning algorithm and an efficient
table transform-based particle swarm optimization (TPSO). This study uses the proposed
method to deal with the large-size TSP routing system.
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Size: 1965056 |
Author: qi |
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Description: 假设在一个供求关系系统中，车辆从货源取货，配送到对应的若干配送点。车辆存在最大载货量，且配送可能有时间限制。需要合理安排取货时间，组织适当的行车路线，使用户需求得到满足，同时使某个代价函数最小，比如总工作时间最少、路径最短等。
可以看出TSP问题是VRP问题的一种简单特殊形式。因此，VRP也是一种NP hard 问题。
目前解决此种问题的办法有多种，主要以启发式算法为主。包括退火算法、遗传算法、蚁群算法、禁忌算法等，本文介绍两种比较简单算法：C-W节约算法和遗传算法。(Assume that in a supply and demand relationship system, the vehicle picks up the goods from the source and delivers them to the corresponding distribution points. There is a maximum amount of cargo in the vehicle and there may be a time limit for delivery. It is necessary to arrange the picking time reasonably, organize the appropriate driving route, and satisfy the user's needs, and at the same time minimize a certain cost function, such as the minimum total working time and the shortest path.
It can be seen that the TSP problem is a simple and special form of the VRP problem. Therefore, VRP is also an NP hard problem.
At present, there are many ways to solve this kind of problem, mainly based on heuristic algorithms. Including annealing algorithm, genetic algorithm, ant colony algorithm, tabu algorithm, etc. This paper introduces two simple algorithms: C-W saving algorithm and genetic algorithm.)
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Size: 4096 |
Author: HappyppaH |
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