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1.1 背包问题
有一个徒步旅行者，已知他能承受的旅行背包的重量不超过a（kg）。设有n种物品可供他选择装入背包，这n种物品分别编号为1，2，…，n。其中第i种物品每件的重量为ai（kg），其使用价值（指一件第i种物品对旅行者来说所带来的好处的一种数量指标）为ci（i＝1，2，…，n）。问这位旅行者应如何选择携带这n种物品的件数，使得总价值最大？
-1.1 knapsack problem is a hikers. he is known to travel to withstand t
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matlab编制的用模拟退火算法解决0-1背包问题的具体实例-matlab prepared using simulated annealing algorithm to solve 0-1 knapsack problem specific examples of
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利用模拟退火解决0-1背包问题，适合初学者。-The use of simulated annealing to solve 0-1 knapsack problem, suitable for beginners.
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模拟退火解决0-1背包问题，初学者可以借鉴-Simulated annealing to solve 0-1 knapsack problem, beginners can learn from
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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 fr
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一个解决0-1背包问题的模拟退火程序，希望给有需要的人帮助-A solution to the 0-1 knapsack problem simulated annealing process, hoping to help those in need
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用matlab实现投资问题（类似于0-1背包问题，但更复杂）的动态规划-Problem with matlab realized investment (like the 0-1 knapsack problem, but more complex) dynamic programming
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用matlab编写的一个解决0-1背包问题，其算法采用粒子群算法-use matlab software write 0-1 knapsack
problem use PSO method
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粒子群算法解决0-1背包问题，对于n个体积为aj、价值分别为cj的物品，如何将它们装入总体积为b的背包中，使得所选物品的总价值最大。-Particle swarm algorithm to solve the 0-1 knapsack problem, for n volume for aj, value for cj items, how they are loaded in the total volume of the backpack, b, making the total value
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matlab求解粒子群，属于0-1背包问题-matlab to solve the particle swarm, belonging to the 0-1 knapsack problem
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solving knapsack 0,1 problem with GA in matlab
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0-1背包问题是学习算法时一个非常常用的简单问题，可以用多种智能优化算法实现，这里用到了蚁群算法和模拟退火算法还有两种方法的结合三种方法来实现。-0-1 knapsack problem is a simple learning algorithm is a very common problem, and can use a variety of intelligent optimization algorithm, ant colony algorithm and simulated ann
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基于量子遗传算法的0-1背包问题matlab-Matlab genetic algorithm based on quantum 0-1 knapsack problem
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KNAPSACK Solves the 0-1 knapsack problem for positive integer weights - dynamic programming
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现代优化算法,蚁群算法解决0-1背包问题-Modern optimization algorithm, ant colony algorithm to solve 0-1 knapsack problem
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0-1背包问题遗传算法，包含精英选择和非精英选择-0-1 knapsack problem algorithms, comprising elite and non-elite choose
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遗传算法解决0-1背包问题，并有其他非遗传算法解决该问题，两种方法功能的对比-Genetic algorithm solve the 0-1 knapsack problem and other approaths to solve the same problem.The comparation of the two methods.
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应用禁忌搜索算法解决0-1背包问题，可以快速得到最优结果，用matlab实现-Application of tabu search algorithm to solve 0-1 knapsack problem, you can quickly get the best results, using matlab realize
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模拟退火算法的应用很广泛，可以较高的效率求解最大截问题(Max Cut Problem)、0-1背包问题(Zero One Knapsack Problem)、图着色问题(Graph Colouring Problem)、调度问题(Scheduling Problem)等等。(Simulated annealing algorithm is widely used, can be more efficient to solve the maximum Problem Cut (Max), 0-1
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利用禁忌搜索算法求解0-1背包问题。禁忌搜索算法相比其他搜索算法更优，设置藐视规则来避免陷入局部最优解。(Solve 0-1 Knapsack Problem based on Tabu search. The tabu search algorithm is superior to other search algorithms and sets contempt rules to avoid falling into local optimal solutions.)
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