Description: 模拟退火算法的MATLAB实例，包含图作色，旅行商等多个问题的例子。-Simulated annealing algorithm of MATLAB examples, including Fig作色, traveling salesman problem, and many other examples. Platform: |
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Author:boy |
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Description: 按自然法则计算的一个新分支：确定性退火技术
解决Job Shop调度问题的模拟退火算法改进-Calculated in accordance with the laws of nature a new branch: deterministic annealing to solve the Job Shop scheduling problem to improve the simulated annealing algorithm Platform: |
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Author:尹胜台 |
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Description: General simulated annealing algorithm-anneal Minimizes a function with the method of simulated annealing (Kirkpatrick et al., 1983)
ANNEAL takes three input parameters, in this order:
LOSS is a function handle (anonymous function or inline) with a loss function, which may be of any type, and needn t be continuous. It does, however, need to return a single value.
PARENT is a vector with initial guess parameters. You must input an initial guess.
OPTIONS is a structure with settings for the simulated annealing. If no OPTIONS structure is provided, anneal uses a default structure. OPTIONS can contain any or all of the following fields (missing fields are filled with default values):
Verbosity: Controls output to the screen.
0 suppresses all output
1 gives final report only [default]
2 gives temperature changes and final report
Generator: Generates a new solution from an old one. Any function handle that takes a solution as input and gives a valid solution (i.e. Platform: |
Size: 4096 |
Author:Ping-Feng Xu |
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Description: 推荐一个实用的Matlab模拟退火工具箱，里面含有非常全的matlab语言模拟退火算法,包括了Matlab函数和6个例程。
-Recommend a practical simulated annealing Matlab toolbox, which contains a very wide of the simulated annealing algorithm matlab language, including the Matlab function and six routines. Platform: |
Size: 208896 |
Author:江泉 |
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Description: 使用VC++实现的俄罗斯方块，有界面，便于操作！-VC++ to achieve the use of simulated annealing algorithm, there are interfaces, easy to operate! Platform: |
Size: 2708480 |
Author:jonguo |
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Description: 一篇关于模拟退火算法解决TSP问题的MATLAB代码，拿来分享，欢迎讨论-On a simulated annealing algorithm to solve TSP problem of MATLAB code, used to share, please discuss Platform: |
Size: 9216 |
Author:Allen |
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Description: 用模拟退火优化遗传算法，使遗传算法具有反向搜索能力，通过仿真表明能够得到更优的值。-Optimization by simulated annealing genetic algorithm, genetic algorithm so that the reverse search capabilities, through the simulation shows that can be better value. Platform: |
Size: 12288 |
Author:史峰 |
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Description: 模拟退火-粒子群算法，该程序将模拟退火算法和粒子群算法相结合，对优化参数有很好的效果-Simulated annealing- particle swarm optimization, the program will be simulated annealing algorithm and particle swarm optimization by combining optimization parameters have a good effect Platform: |
Size: 1024 |
Author:liwei |
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Description: 运用模拟退火算法求解带时间窗约束的车辆路径问题-The use of simulated annealing algorithm with time window constrained vehicle routing problem Platform: |
Size: 2407424 |
Author:before |
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Description: 模拟退火算法是基于蒙特卡罗迭代求解法的一种启发式随机搜索过程。本文给出了该算法的详细介绍和伪代码。-Monte-Carlo simulated annealing algorithm is based on a heuristic iterative method for solving stochastic search process. This paper gives a detailed description of the algorithm and pseudo code. Platform: |
Size: 5120 |
Author:Royal |
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Description: 这是用模拟退火算法解决0-1背包问题，下载后可直接运行，可以帮助有需要对模拟退火算法进行了解的朋友。-This is a simulated annealing algorithm to solve the 0-1 knapsack problem, after downloading, can be directly run, you can help those in need of the simulated annealing algorithm to find out about friends. Platform: |
Size: 1024 |
Author:小吴 |
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Description: 模拟退火GUI演示，利用模拟退火算法求全局最大值最小值-Simulated annealing GUI demonstration, the use of simulated annealing algorithm seeking the global maximum value of the minimum Platform: |
Size: 30720 |
Author:junlin |
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Description: TSP can be defined as a problem where starting from a node it is required to visit every other node only once in a way that the total distance covered is minimized. After an initial solution a neighborhood solution is selected by an exchange of a randomly selected pair of nodes. The randomly generated neighbor solution is selected if it improves the solution else it is selected with a probability that depends on the extent to which it deteriorates from the current solution.-TSP can be defined as a problem where starting from a node it is required to visit every other node only once in a way that the total distance covered is minimized. After an initial solution a neighborhood solution is selected by an exchange of a randomly selected pair of nodes. The randomly generated neighbor solution is selected if it improves the solution else it is selected with a probability that depends on the extent to which it deteriorates from the current solution. Platform: |
Size: 13312 |
Author:amilcar |
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Description: Simulated Annealing (SA) is a smart (meta)-heuristic for Optimization. Given a cost function in a large search space, SA replaces the current solution by a random "nearby" solution. The nearby solution is chosen with a probability that depends on the difference between the corresponding function values and on a global parameter T (a.k.a the temperature). T is gradually decreased during the process. The current solution changes almost randomly when T is large, but increasingly "downhill" as T goes to zero. The allowance for "uphill" moves saves the method from becoming stuck at local minima.
This approach has some similitude with Physic, where the heat causes the atoms to become unstuck from their initial positions and wander randomly through states of higher energy the slow cooling gives them more chances of finding configurations with lower internal energy than the initial one.-Simulated Annealing (SA) is a smart (meta)-heuristic for Optimization. Given a cost function in a large search space, SA replaces the current solution by a random " nearby" solution. The nearby solution is chosen with a probability that depends on the difference between the corresponding function values and on a global parameter T (aka the temperature). T is gradually decreased during the process. The current solution changes almost randomly when T is large, but increasingly " downhill" as T goes to zero. The allowance for " uphill" moves saves the method from becoming stuck at local minima. This approach has some similitude with Physic, where the heat causes the atoms to become unstuck from their initial positions and wander randomly through states of higher energy the slow cooling gives them more chances of finding configurations with lower internal energy than the initial one. Platform: |
Size: 20480 |
Author:dingchong |
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Description: this journal is created by Sachin Jayaswal Student ID: 20186226 Department of Management Sciences
University of Waterloo.
it s describe how performances of tabu search and simulated annealing solve the TSP. this journal includes tabu search and SA matlab code to solve tsp. Platform: |
Size: 74752 |
Author:destra |
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Search - Simulated Annealing