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Description: 求解tsp问题的局部优化算法-the local optimization algorithm
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Size: 21842 |
Author: 曲晓威 |
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Description: TSP算法，应用局部搜索法得到最优路径，已经经过优化。没有密码，可以使用，vc环境下使用。-TSP algorithm, using local search to be optimal path has been optimized. No password can be used, vc environments.
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Size: 29999 |
Author: 霍哲 |
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Description: 本Java程序实现了Combinatorial Algorithms: Theory and Practice", by Reingold, Nievergelt and Deo 讨论的基于edge splitting 的分支定界算法，同时提供了一个简单的分支定界算法和一个基于local search的算法作对比
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Size: 2275274 |
Author: yangwang5 |
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Description: 求解tsp问题的局部优化算法-the local optimization algorithm
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Size: 45056 |
Author: 曲晓威 |
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Description: TSP算法，应用局部搜索法得到最优路径，已经经过优化。没有密码，可以使用，vc环境下使用。-TSP algorithm, using local search to be optimal path has been optimized. No password can be used, vc environments.
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Size: 1357824 |
Author: 霍哲 |
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Description: 用禁忌算法求解tsp（旅行商问题）具有速度快，收敛性好，不易陷入局部最优解等特点-Algorithm with the taboo tsp (TSP) has fast convergence, and not easily trapped into local optimal solution, etc.
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Size: 988160 |
Author: 张聪誉 |
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Description: TSP问题是组合优化中的经典问题。其解决方法有局部优化方法和一些启发式算法,局部搜索方法充分考虑问题
的邻域结构,遗传算法有很好的全局搜索能力,memetic算法把遗传算法和局部优化算法相结合,试验结果证明,能很好地解
决TSP问题。-TSP problem is a classic combinatorial optimization problem. Its solution has a number of local optimization methods and heuristic algorithms, local search methods take full account of the issue of neighborhood structure, genetic algorithm has good ability of global search, memetic algorithm for the genetic algorithm and local optimization algorithm combining test results proved that well positioned to solve the TSP problem.
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Size: 102400 |
Author: 文龙 |
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Description: Solve TSP by local approximation
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Size: 36864 |
Author: Sasha |
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Description: 将局部优化算子引入遗传算法求解TSP问题，以求提高算法的性能。具体措施是在标准遗传算法的最后阶段增加步，即对每代的最优个体进行一定次数的局部搜索，以求改善该最优个体。首先提出将反序一杂交法引入局部优化过程中。
同几种‘常用的局部优化力一法相比，反序一杂交法的性能最为突出。实验结果表明，该优化力一法能有效求解300个城市以内的
TSP问题。
-Will introduce a local optimization operator TSP problem genetic algorithm, in order to increase the performance of algorithm. Specific measures in the standard genetic algorithm to increase the final phase of step-by-step, that is optimal for each individual to carry out on behalf of a certain number of local search, in order to improve the best individual. First put forward the anti-sequence hybridization to introduce a local optimization process. With several ' common edge of a local optimization method, the anti-sequence of a hybridization of the most outstanding performance. Experimental results show that the optimization method can effectively force a solution of 300 cities within the TSP problem.
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Size: 43008 |
Author: JONE |
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Description: 模拟退火和对称
*欧几里德旅行商问题。
*
*为基础的解决办法的本地搜索启发式
*非过境道路和近邻
-/*
* Simulated annealing and the Symetric
* Euclidian Traveling Salesman Problem.
*
* Solution based on local search heuristics for
* non-crossing paths and nearest neighbors
*
* Storage Requirements: n^2+4n ints
*
* Problem: given the coordinates of n cities in the plane, find a
* permutation pi_1, pi_2, ..., pi_n of 1, 2, ..., n that minimizes
* sum for 1<=i<n D(pi_i,pi_i+1), where D(i,j) is the euclidian
* distance between cities i and j
*
* Note: with n cities, there is (n-1)!/2 possible tours.
* factorial(10)=3628800 factorial(50)=3E+64 factorial(150)=5.7E+262
* If we could check one tour per clock cycle on a 100 MHZ computer, we
* would still need to wait approximately 10^236 times the age of the
* universe to explore all tours for 150 cities.
*
* gcc-O4-o tsp tsp.c-lm tsp | ghostview-
*
* Usage: tsp [-v] [n=dd] [s=dd] [filename]
* -v : verbose
* n= : nb of cities (cities generated randomly on E^2
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Size: 86016 |
Author: 孙博 |
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Description: 提出一种改进的禁忌搜索算法来求解背包问题。该算法基于禁忌搜索技术,并采用I&D策略,同时设计了两种针对局
部最优解的变异算子。改进后的算法能有效地弥补标准禁忌算法对初始解依赖的缺陷,同时也避免了搜索停滞的现象。通过对具
体实例和随机问题的测试,表明改进后的禁忌搜索算法有更好的性能。
关-An improved tabu search algorithm to solve knapsack problem. The algorithm is based on tabu search techniques, using I & D strategies, while designed for the local optimal solution of the two kinds of mutation operator. The improved algorithm can effectively compensate for the standard tabu search algorithm depends on the initial solution defect, but also to avoid the phenomenon of search stagnation. Through specific examples and random-question test, indicating that the improved tabu search algorithm has better performance. Guan
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Size: 6144 |
Author: logspace |
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Description: A paper of Guided Local Search
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Size: 791552 |
Author: Abdullah |
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Description: 1 以10/30个结点的TSP问题为例,用遗传算法加以求解；
2 掌握遗传算法的基本原理、各个遗传操作和算法步骤；
3 能求出问题最优解，若得不出最优解，请分析原因；
4 要求界面显示每次迭代求出的局部最优解和最终求出的全局最优解。-For example, 1 to 10/30 junction TSP problem with a genetic algorithm to solve 2 mastered the basic principles of the genetic algorithm, various genetic manipulation, and algorithm steps 3 can solve for the optimal solution, if was not optimal solutions, analyze the reasons 4 interface displays each iteration obtained local optimal solution and ultimately find the global optimum solution.
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Size: 3072 |
Author: soli |
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Description: Simulated Annealing (SA) is the oldest probabilistic
meta-heuristic algorithm and one of the first algorithms
having ability to avoid being trapped in local minima. It
is inspired by the process of annealing in metallurgy. In
this process a material is heated and slowly cooled into
solid crystal state with minimum energy and larger
crystal size to reduce defects in metallic structures. Once
the system has cooled, the configuration will represent a
sample at or close to a global optimum.
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Size: 2048 |
Author: sorayya |
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Description: Ant Colony Optimization Algorithm (ACO) and TSP
ACO algorithm mimics the behavior of real life ants and on how they interact with each other. The basic philosophy of the algorithm involves the movement of a colony of ants through the different states of the problem influenced by two local decision policies, viz., trails and attractiveness and two mechanisms, viz., trail evaporation and daemon actions. The algorithm aims to search for an optimal path based on the behavior of ants seeking a path between their colony and a source of food. Thereby, each such ant incrementally constructs a solution to the problem.
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Size: 14336 |
Author: sorayya |
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Description: TSP问题，是一个多局部最优的最优化问题：有n个城市，一个推销员要从其中某一个城市出发，唯一走遍所有的城市，再回到他出发的城市，求最短的路线。-TSP, is more than one local optimum optimization problem: There are n cities, where a salesman one city starting only traveled all the cities, and then returned to his departure city, seeking the shortest route.
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Size: 2048 |
Author: 梁超 |
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Description: 自适应离散粒子群算法求解TSP问题，包含有三个基本实例，其中含扰动变量可防止陷入局部最优-Adaptive particle swarm optimization for TSP, contains three basic example, which prevents the disturbance variable containing local optimum
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Size: 4096 |
Author: 冬冬东 |
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Description: tsp问题（全称：TravellingSalesmanProblem），又称为旅行商问题、货郎担问题、TSP问题，是一个多局部最优的最优化问题，遗传算法是一种基于种群演变一种优化的算法，在此基础上的优化程序会自动寻找出最短路(TSP (full name: TravellingSalesmanProblem), also known as the traveling salesman problem, traveling salesman problem, but TSP problem is an optimization problem of multi local optimum, genetic algorithm is an optimization algorithm based on the evolution of a population, on the basis of the optimization program will automatically find the shortest path)
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Size: 146432 |
Author: 淡然踏歌
|
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Description: TSP问题（旅行商问题），用遗传算法解决TSP问题，得到问题的最优解，是局部最优解。(TSP problem (traveling salesman problem), using genetic algorithm to solve TSP problem, get the optimal solution of the problem, is the local optimal solution.)
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Size: 13312 |
Author: yaru
|
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Description: vehicle routing lecture
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Size: 148480 |
Author: chehab.salah |
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