# 01 2 f

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### 01 backpack, full backpack, multiple backpack, and mixed backpack Problems

01 backpack, full backpack, multiple backpack, and mixed backpack Problems P01: 01 backpack Problems Question There are n items and a backpack with a capacity of v. The cost of the I-th item is C [I], and the value is W [I]. Solving which items are

### Knapsack Problem tutorial-01 backpack, full backpack, multiple backpacks, hybrid backpack favorites

P01: 01 backpack ProblemsQuestionThere are n items and a backpack with a capacity of v. The cost of the I-th item is C [I], and the value is W [I]. Solving which items are loaded into a backpack can maximize the total value. Basic IdeasThis is the

### The most understandable 01 backpack in history, full backpack, multi-backpack explanation

Backpack 01 Backpack, full backpack, multi-backpack detailed PS: We feel that the writing is passable, help me to the top of the blog, thank you. First of all, dynamic planning, dynamic planning this thing and recursion, can only find local

### Hdu1864_ maximum reimbursement amount (Backpack/01 backpack), HDU1864 backpack

Hdu1864_ maximum reimbursement amount (Backpack/01 backpack), HDU1864 backpack Solution report Question Portal #include #include #include #include #define inf 99999999using namespace std;int v,w[35],d[4],dw1,sum,dp[31*1000*100];int main(){

### 01 Backpack Java Implementation (beginner to proficient)

One, what is 01 backpack 　　01 The backpack is a few pieces of m items in the space W backpack, each item volume of W1,W2 to WN, corresponding to the value of P1,P2 to PN. 01 Backpack is the simplest problem in knapsack problem. 01 Backpack

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### Backpack 9 lecture 01 backpack (zeroonepack)

I recently read about the 9-story backpack. We need to carefully study this kind of White Paper. Because there are some thinking jumps in it, we need to add our own understanding on the basis of the original article. Question There are n items and a

### A brief talk on "algorithm micro-interpretation" 01 Fractional planning

Elementary Introduction to 01 fractional planningThe so-called 01 score plan, see this name, may think of 01 backpack, actually grow similar.This algorithm is required to "cost-effective" the highest solution. Sum (v)/sum (W) the highest solution.

### Backpack 01 Backpack, full backpack, multi-backpack detailed

First of all, dynamic planning, dynamic planning this thing and recursion, can only find local relations, if you want to all listed, it is difficult, such as Hanoi. You can say that all the other layers except the last layer are moved to 2, and then

### "Dynamic Planning" knapsack problem (i) 01 backpack full Backpack Multiple backpack

One, 01 backpackThere are n items and a backpack with a capacity of V. The price of item I (i.e. volume, hereinafter) is w[i], the value is c[i]. The solution of which items are loaded into the backpack allows the sum of the costs of these items to

### Explanation of backpack 01, full, and multiple

Explanation of backpack 01, full, and multiple   PS: If you think you can write well, just help me pin my blog. Thank you. First, let's talk about dynamic planning. Dynamic Planning is just like recursion. We can only find local relationships.

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