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【Mathimatics-Numerical algorithms】上大_net-0-1背包问题(回朔法) DL : 0: 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 solve the problem, and will be used backtracking algorithm to solve the problem. As to the choice of a subset of object, they will load a backpack, in order to obtain the greatest profits, the solution should be organized into space subset of the shape of the tree (Figure 1 6-2 below). The backtracking algorithms and 4. Two loading problem is very similar. Forming a recursive algorithm to get the maximum benefit available. Then, this algorithm is modified to form code. Improved code can be found at the maximum benefits included in the backpack of a collection of objects.
Update : 2024-05-05 Size : 8192 Publisher : 周易
【Mathimatics-Numerical algorithms】 my0-1knapsack DL : 0: 给定n 个物品, 物品i重为wi 并且价值为 vi ，背包所能承载的最大容量为 W. 0-1 背包问题即是选择含有着最大总价值的物品的子集且它的容量 ≤W ．用动态规划实现-given n goods, items i weight of wi and value of vi, the backpack can carry a maximum capacity of W. 0-1 knapsack problem that is a choice with a maximum total value of the goods but a subset of the W capacity. Dynamic Programming
Update : 2024-05-05 Size : 1024 Publisher : 叶黎
【Data structs】贪婪算法解决背包 DL : 0: 运用贪婪算法能够很好解决0/1背包问题，这是我编的一个小程序，运行过很好。-greedy algorithm can be used to solve a very good 0/1 knapsack problem, this is my part of a small program running very good.
Update : 2024-05-05 Size : 1024 Publisher : 应吉平
【Data structs】背包问题的两种算法实现 DL : 0: 本例编程实现背包问题的递归和非递归算法，让你彻底了解这种算法-the cases Programming knapsack problem of recursive and non- recursive algorithm, so you thoroughly understand this algorithm
Update : 2024-05-05 Size : 13312 Publisher : 朱南辉
【Windows Develop】背包问题递归算法 DL : 0: 背包问题的递归算法，以C语言原代码给出，有需要的朋友可以下载，不许要帐号，自由下载。-knapsack problem recursive algorithm to the original C language code is given, a friend in need can be downloaded allowed to account, free download.
Update : 2024-05-05 Size : 1024 Publisher : 王少石
【Windows Develop】背包问题之贪婪算法求解C语言源代码) DL : 0: 背包问题的贪婪算法，需要的下，不需要帐号的，自由的下。-knapsack problem of greedy algorithm, need, need not account, free under.
Update : 2024-05-05 Size : 1024 Publisher : 王少石
【Data structs】 01背包问题 DL : 0: 采用分枝限界法解决0/1背包问题! 本人上机实习作业,通过老师验收,合格! 针对部分上机实习的同学可以来下~-used Branch and Bound France 0/1 knapsack problem! I practice on the machine operations, acceptance by the teachers, qualified! In view of the attachment on the machine for students to the next ~
Update : 2024-05-05 Size : 1024 Publisher : 张锐
【CSharp】背包问题祥解 DL : 0: 背包问题详细解释，很简单，没有密码直接解压-knapsack problem detailed explanation is quite simple and not directly extracting passwords
Update : 2024-05-05 Size : 220160 Publisher : 马侯林
【AI-NN-PR】 GA_01Knap DL : 0: 用遗传算法解决背包问题，可以求最优解，也可以自己设定次数-using genetic algorithms to solve knapsack problem, the optimal solution can help, can set its own number
Update : 2024-05-05 Size : 2065408 Publisher :
【Other】 algrithm DL : 0: 算法设计与分析的经典程序，主要有0-1背包问题，最小生成树等。-algorithm design and analysis of the classic procedure, mainly 0-1 knapsack problem, such as minimum spanning tree.
Update : 2024-05-05 Size : 6144 Publisher : jun
【matlab】 mathmodel2 DL : 0: 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 the weight of the backpack not exceed a (kg). N Species with articles for his choice loaded backpack, n product were numbered 1, 2, ..., n. I first of which product each ai of the weight (kg), its value (i refers to a section of the types of items travelers the benefits brought by a number of indicators) for the ci (i = 1, 2, ..., n). Asked how travelers who choose to bring this product to the n pieces, making the total value of the largest?
Update : 2024-05-05 Size : 13312 Publisher : 孙竟飞
【Data structs】 fjdjf DL : 0: 用分支界限法解决的几个问题:包括0-1背包问题,最大团问题,电路布线问题,最大装载问题.作业最优处理问韪.-branch line with the law to solve several problems : including 0-1 knapsack problem, the largest group, circuit wiring problem, the greatest problem loading. Optimal handling operations Q premises.
Update : 2024-05-05 Size : 59392 Publisher : michael
【Other】 tigongyuanma DL : 0: 该文件包共有5个文件 TSP--传统算法---说明TSP的传统算法实践背包问题----0-1背包问题的传统算法实践模拟退火算法----模拟退火算法实现TSP问题我的通讯录----我整理写的个人通讯录遗传算法----遗传算法解决TSP问题 -The package total of five documents TSP- traditional algorithms--- algorithms that TSP practice traditional knapsack problem---- 0-1 knapsack problem of the traditional practice of simulated annealing algorithm algorithm simulated annealing algorithm---- TSP I---- I am finishing the Address Book Personal Address Book written---- genetic algorithm genetic algorithm to solve TSP problems
Update : 2024-05-05 Size : 10829824 Publisher : lisanshi2006
【AI-NN-PR】 vb_Calculator DL : 0: 基于遗传算法的背包问题求解，有基本的说明和代码-based on genetic algorithm knapsack problem solving, a basic description and code.
Update : 2024-05-05 Size : 20480 Publisher : 赵宇
【Console】 myknapsack DL : 0: a) 0-1背包问题采用的是动态规划法,该算法思想简介如下: 有些问题常常没有办法把它们分成较小数目的子问题，在这种情况下，可以试着把问题分成必要多的子问题，每个子问题又可以分成数目不确定的必要多的子子问题，这样就会产生大量的子问题。如果分得的子问题界限不清，互相交叉，则在大量的子问题中会存在一些完全相同的子问题，因而在解这类问题时，将可能重复多次解同一个子问题。这种重复当然是不必要的，避免的方法可以在解决一个子问题后把它的解（包括其子子问题的解）保留下来，若遇到求解与之相同的子问题的时候，就可以把它找出来直接使用。为解问题而将它的子问题的解填入表中以待需要时直接查除了使用，这样的方法就是动态规划法。 b) 分数背包问题采用的是贪心选择法,该算法思想简介如下: 贪心算法总是作出在当前看来是最好的选择。也就是说，不从整体最优上加以考虑，它所做出的仅是在某种意义上的局部最优解。 -a) 0-1 knapsack problem is the use of dynamic programming method, the algorithm Thought as follows : some of the problems often no way to put them into a smaller number of sub-issues, in such circumstances, it attempts problem into the necessary number of sub- problems, every child that the problem can be divided into a number of uncertainties over the need for the children, this will have a lot of the problem. If the share of the sub- problems ill-defined, overlapping, in a large number of sub-issues there will be some identical son, thus the solution of such problems, it will be possible to repeat the same number of sub- problems solution. Such duplication is unnecessary. avoid the method can solve a problem for it to the solution (including his son, son of FNL) remain, if faced with
Update : 2024-05-05 Size : 1024 Publisher : 林茜
【Data structs】 01knap_Dynamic_Programming DL : 0: 本文通过研究动态规划原理，提出了根据该原理解决０／１背包问题的方法与算法实现，并对算法的正确性作了验证．观察程序运行结果，发现基于动态规划的算法能够得到正确的决策方案且比穷举法有效．-through research paper on dynamic programming, According to the principle of resolving the 0/1 knapsack problem with the algorithm, the algorithm was verified the correctness. Observation running findings, based on dynamic programming algorithm can be the correct decision than a program exhaustive method effective.
Update : 2024-05-05 Size : 10240 Publisher : 汤烈
【Data structs】 bbwt DL : 0: 自己随便写的大家看看最好有人帮我写个回溯算法0-1背包问题的演示软件 -own writing any of us look at the best people to help me write a backtracking algorithm 0-1 knapsack problem of presentation software
Update : 2024-05-05 Size : 1024 Publisher : 手电筒
【Data structs】 PackageProblem DL : 0: 实现背包问题 package problem 1．问题描述假设有一个能装入总体积为T的背包和n件体积分别为w1 , w2 , … , wn 的物品，能否从n件物品中挑选若干件恰好装满背包，即使w1 +w2 + … + wn=T，要求找出所有满足上述条件的解。例如：当T=10，各件物品的体积{1，8，4，3，5，2}时，可找到下列4组解：（1，4，3，2）、（1，4，5）、（8，2）、（3，5，2）。 2．基本要求读入T、n、w1 , w2 , … , wn 3．提示：可利用递归方法：若选中w1 则问题变成在w2 , … , wn 中挑选若干件使得其重量之和为T- w1 ，若不选中w1，则问题变成在w2 , … , wn 中挑选若干件使得其重量之和为T 。依次类推。也可利用回溯法的设计思想来解决背包问题。首先将物品排成一列，然后顺序选取物品装入背包，假设已选取了前i 件物品之后背包还没有装满，则继续选取第i+1件物品，若该件物品“太大”不能装入，则弃之而继续选取下一件，直至背包装满为止。但如果在剩余的物品中找不到合适的物品以填满背包，则说明“刚刚”装入背包的那件物品“不合适”，应将它取出“弃之一边”，继续再从“它之后”的物品中选取，如此重复，，直至求得满足条件的解，或者无解。注：没压缩密码-knapsack problem achieve a package problem. Problem description one would assume that the total volume of loaded backpack and T n size pieces of w1, w2, ..., wn items Can n items from the selected pieces were just filled with backpacks, even w1 w2 ... wn = T, asked to identify all of the above conditions are met solution. For example : when T = 10, the volume of items (1,8,4,3,5,2), may find the following four solutions : (1,4,3,2), (1,4,5), (8,2), (3,5,2). 2. Basic requirements read T, n, w1, w2, ..., wn 3. Tip : Recursive methods can be used : If the problem were selected w1 into the w2, ..., wn selected several pieces make its weight and as a T-w1, if selected w1, w2 issue into the .... wn selected several pieces make its weight and as T. Renumbered accordingly. Retrospective can also u
Update : 2024-05-05 Size : 9216 Publisher : 李昭明
【AI-NN-PR】 simulate_knapsack DL : 0: 下面是模拟退火算法的代码,使用模拟退火算法（SAA）解决0－1背包问题 -Below are simulated annealing algorithm code, the use of simulated annealing algorithm (SAA) 0-1 knapsack problem solving
Update : 2024-05-05 Size : 1024 Publisher : 水水
【Data structs】 dongtaiguihua DL : 0: 动态规划算法的一个实例，解决0-1背包问题-dynamic programming algorithm an example to solve 0-1 knapsack problem
Update : 2024-05-05 Size : 1024 Publisher : 刘永峰

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