搜索资源列表
0-1背包的回溯算法
- 回溯法解决0-1背包问题-Backtracking 0-1 knapsack problem solving
0-1背包的动态规划算法
- 动态规划0-1背包问题-Dynamic Programming 0-1 knapsack problem
0-1背问题
- 0-1背包问题 可以提供在背包方面遇到问题的学生或者有需要的人.-0-1 knapsack problem can provide a backpack problems encountered students or those who are in need.
上大_net-0-1背包问题(回朔法)
- 0 / 1背包问题是一个N P-复杂问题，为了解决该问题，，将用回溯算法解决该问题。既然想选择一个对象的子集，将它们装入背包，以便获得的收益最大，则解空间应组织成子集树的形状（如图1 6 - 2所示）。该回溯算法与4 . 2节的装载问题很类似。首先形成一个递归算法，去找到可获得的最大收益。然后，对该算法加以改进，形成代码。改进后的代码可找到获得最大收益时包含在背包中的对象的集合。-0 / 1 knapsack problem is a P-complex issues, in order to
knapsack.rar
- 用GAlib库实现的解决0/1背包问题的遗传算法程序源代码。, Solution 0/1 knapsack question heredity algorithm procedure source code realizes which with the GAlib storehouse.
knapsack
- 0—1背包问题的五种解法 1贪心法 2动态规划 3回溯 4分支限界 5遗传算法-0-1 knapsack problem greedy algorithm five Solution 1 2 3 back in 4 dynamic programming genetic algorithm branch and bound 5
Knapsack
- 我自己做的一个0-1背包问题程序 用回溯法 做的 望大家分享 请指正-I own a 0-1 knapsack problem with retroactive law procedures do hope to share, please correct me
0-1-knapsack-problem
- 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
0-1
- 在0 / 1背包问题中，需对容量为c 的背包进行装载。从n 个物品中选取装入背包的物品，每件物品i 的重量为wi ，价值为pi 。对于可行的背包装载，背包中物品的总重量不能超过背包的容量，最佳装载是指所装入的物品价值最高。-At 0/1 knapsack problem, there is a need for a capacity of c to load the backpack. N items from a selected items into the backpack, each i
KnapsackProblem
- 0/1背包问题的几种解法，包括回溯法、动态规划法以及穷举法。另外还包括集中方法的一个测试报告。-0/1 knapsack problem several solutions, including backtracking, dynamic programming method and the exhaustive method. It also includes a focus on methods of test reports.
0-1knapsack_problem
- 0/1背包问题：给定n种物品和一个容量为C的背包，物品i的重量是wi，其价值为vi，0/1背包问题是如何选择装入背包的物品（物品不可分割），使得装入背包中物品的总价值最大?回溯法解决0/1背包问题-0/1 knapsack problem: given n types of items and a knapsack of capacity C, the weight of item i is wi, the value of vi, 0/1 knapsack problem is how to
Knapsack
- 0-1背包 给定n种物品和一背包。物品i的重量是wi，其价值为vi，背包的容量为c。问应如何选择装入背包中的物品，使得装入背包中物品的总价值最大？
0-1
- 0-1背包问题的动态规划，根据算法书上自己编写的一个小程序，背包问题用动态规划的方法来解决-0-1 knapsack problem dynamic programming, according to algorithm I have written the book on a small program, knapsack problem using dynamic programming approach to the
Backtrack_0-1bag
- 从文件读入数据，用回溯法实现了0-1背包最优解的问题-Read data from a file, using backtracking to achieve the optimal solution of the 0-1 knapsack problem
0-1
- 0-1背包问题， 给定一个载重量为m，n个物品，其重量为wi，价值为vi，1<=i<=n，要求:把物品装入背包，并使包内物品价值最大-0-1 knapsack problem, given a load for the m, n one item, the weight wi, the value of vi, 1 < = i < = n, asked: the items into backpacks, and to bag the maximum value of the
0-1-knapsack-problem
- 01背包是在M件物品取出若干件放在空间为W的背包里，每件物品的体积为W1，W2……Wn，与之相对应的价值为P1,P2……Pn。求出获得最大价值的方案。在本例中所有数值均为整数-01 M items in the backpack is out of a number of pieces on the space W of the backpack, the size of each item as W1, W2 ... ... Wn, corresponding to the value of
0-1-knapsack-problem-solution
- 这是一个关于0-1背包问题算法的编程实现，包括了动态规划、分支界限、回溯、贪心算法-This is a 0-1 Knapsack Problem programming, including dynamic programming, branch and bound, backtracking, greedy algorithm
ts-solve-0-1-knapsack-a-info
- 用禁忌搜索解决0-1背包问题，及一些关于禁忌搜索优化和并行处理的资料-Tabu search to solve 0-1 knapsack problem, and some information on tabu search optimization and parallel processing of data
0-1-Knapsack-problem
- 本次实验选择0-1背包问题作为题目，通过使用动态规划、回溯法和分支定界法等算法来求解该问题，从而进一步的了解各种算法的原理、思路及其本质，深化对算法的了解，锻炼自己对各种算法的分析和使用，熟悉软件底层算法和界面编程。-The 0-1 knapsack problem was chosen as the subject, through the use of dynamic programming, backtracking and branch and bound method algorit
应用禁忌搜索算法解决0-1背包问题
- 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.)