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1. Top results related to divide and conquer

   • divide and conquer and recursion

     Top Answer

     Answered Feb 12, 2010 · 26 votes

     "Always" is a scary word, but I can't think of a divide-and-conquer situation in which you couldn't use recursion. It is by definition that divide-and-conquer creates subproblems of the same form as the initial problem - these subproblems are continually broken down until some base case is reached, and the number of divisions correlates with the size of the input. Recursion is a natural choice for this kind of problem.

     See the Wikipedia article for more good information.

     Other Answers

     Answered Feb 12, 2010 · 8 votes

     A Divide-and-conquer algorithm is by definition one that can be solved by recursion. So the answer is yes.

     Other Answers

     Answered Feb 12, 2010 · 1 votes

     Usually, yes! Merge sort is an example of the same. Here is an animated version of the same.

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     1/5

   • Divide and conquer paradigm and recursion in C - Merge sort example

     Top Answer

     Answered Jul 04, 2013 · 2 votes

     I am not sure why you are asking people to make you understand the algorithm. I can just assist you you but you have to go through it.

     In merge short you have to cut the array in two pieces. suppose you have 10 elements then high=0 and low=10-1=1. mid = (9+0)/2 = 4. So, you have divided the main array to 2 parts from 1th element to 5th and from 6th element to 10th (1..10). When ever you have more than one element in a piece you cut it into two again. At the end merge them i.e. add arrays again but in ascending order. Finally you get a single array sorted. Its very tough to explain every piece. I think this link from wiki can help. http://en.wikipedia.org/wiki/Merge_sort

     Now comes the function calling. main function is calling merge_sort it will pass low and hight (the full range of array) but within this function the merge_sort will be called by himself twice with first half range (starting to mid way and after midway to last element). Each call will again do the same (divide the array and call with first half and send half). This process will go on. merge function will add the array in sorted manner. Thats all you need. If you are not clear print or debug the value of parameters.

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     2/5

   • Divide and conquer, dynamic programming and greedy algorithms!

     Top Answer

     Answered Nov 23, 2016 · 8 votes

     When I have a problem with optimal substructur and no subproblem shares subsubproblems then I can use a divide and conquer algorithm to solve it?

     Yes, as long as you can find an optimal algorithm for each kind of subproblem.

     But when the subproblem shares subsubproblems (overlapping subproblems) then I can use dynamic programming to solve the problem?

     Is this correct?

     Yes. Dynamic programming is basically a special case of the family of Divide & Conquer algorithms, where all subproblems are the same.

     And how is greedy algorithms similar to dynamic programming?

     They're different. Dynamic programming gives you the optimal solution. A Greedy algorithm usually give a good/fair solution in a small amount of time but it doesn't assure to reach the optimum.

     It is, let's say, similar because it usually divides the solution construction in several stages in which it takes choices that are locally optimal. But if stages are not optimal substructures of the original problem, then normally it doesn't lead to the best solution.

     EDIT:

     As pointed out by @rrenaud, there are some greedy algorithms that have been proven to be optimal (e.g. Dijkstra, Kruskal, Prim etc.). So, to be more correct, the main difference between greedy and dynamic programming is that the former is not exhaustive on the space of solutions while the latter is. In fact greedy algorithms are short-sighted on that space, and each choice made during solution construction is never reconsidered.

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     3/5

   • Divide and Conquer Closest Pair Algorithm

     Top Answer

     Answered Apr 15, 2016 · 1 votes

     Use the following method with the change for minDisSimple. You can get more performance.

     static double minDisSimple() { // A straightforward method for computing the distance // of the two closest points in plane[0..N-1].- // to be completed double midDis = Double.POSITIVE_INFINITY; double temp; for (int i = 0; i < N - 1; i++) { for (int j = i + 1; j < N; j++) { temp = plane[i].distance(plane[j]); if (temp < midDis) { midDis = temp; } } } return midDis;}

     Performance wise for small amount of points simple method is good but larger amount of points Divide and Conquer is good. Try number of points with 10, 100, 1000, 10000, 100000, 1000000.

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     4/5

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2. www.geeksforgeeks.org › divide-and-conquerDivide and Conquer Algorithm - GeeksforGeeks

   www.geeksforgeeks.org › divide-and-conquer

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   Apr 30, 2024 · Divide and Conquer algorithm is a problem-solving strategy that involves breaking down a complex problem into smaller, more manageable parts, solving each part individually, and then combining the solutions to solve the original problem.

3. en.wikipedia.org › wiki › Divide-and-conquer_algorithmDivide-and-conquer algorithm - Wikipedia

   en.wikipedia.org › wiki › Divide-and-conquer_algorithm

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   In computer science, divide and conquer is an algorithm design paradigm. A divide-and-conquer algorithm recursively breaks down a problem into two or more sub-problems of the same or related type, until these become simple enough to be solved directly.

4. www.programiz.com › dsa › divide-and-conquerDivide and Conquer Algorithm - Programiz

   www.programiz.com › dsa › divide-and-conquer

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   A divide and conquer algorithm is a strategy of solving a large problem by breaking the problem it into smaller sub-problems, solving the sub-problems and combining them to get the desired output. In this tutorial, you will understand the working of divide and conquer approach with an example.

5. www.khanacademy.org › computing › computer-scienceDivide and conquer algorithms (article) | Khan Academy

   www.khanacademy.org › computing › computer-science

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   Divide-and-conquer. Both merge sort and quicksort employ a common algorithmic paradigm based on recursion. This paradigm, divide-and-conquer, breaks a problem into subproblems that are similar to the original problem, recursively solves the subproblems, and finally combines the solutions to the subproblems to solve the original problem.

6. www.freecodecamp.org › news › divide-and-conquerDivide and Conquer Algorithm Meaning: Explained with Examples

   www.freecodecamp.org › news › divide-and-conquer

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   Nov 26, 2019 · Divide and Conquer is an algorithmic paradigm (sometimes mistakenly called "Divide and Concur" - a funny and apt name), similar to Greedy and Dynamic Programming. A typical Divide and Conquer algorithm solves a problem using the following three steps.

7. www.youtube.com › watchDivide and Conquer: The Art of Breaking Down Problems ...

   www.youtube.com › watch

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   Divide and Conquer is a powerful algorithmic paradigm that breaks down complex problems into smaller, more manageable subproblems. By conquering each subproblem individually and then merging...

   • Video Duration: 11 min
   • Views: 29.5K

   • Author: WilliamFiset

8. brilliant.org › wiki › divide-and-conquerDivide and Conquer | Brilliant Math & Science Wiki

   brilliant.org › wiki › divide-and-conquer

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   Divide and conquer is a powerful algorithm design technique used to solve many important problems such as mergesort, quicksort, calculating Fibonacci numbers, and performing matrix multiplication.

9. People also ask

   What is divide and conquer?

   • Divide and conquer is a way to break complex problems into smaller problems that are easier to solve, and then combine the answers to solve the original problem.

   Divide and Conquer | Brilliant Math & Science Wiki

   brilliant.org/wiki/divide-and-conquer/

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   What is a divide and conquer algorithm?

   • In computer science, divide and conquer is an algorithm design paradigm. A divide-and-conquer algorithm recursively breaks down a problem into two or more sub-problems of the same or related type, until these become simple enough to be solved directly. The solutions to the sub-problems are then combined to give a solution to the original problem.

   Divide-and-conquer algorithm - Wikipedia

   en.wikipedia.org/wiki/Divide-and-conquer_algorithm

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   What is a divide and conquer paradigm?

   • The divide-and-conquer paradigm is often used to find an optimal solution of a problem. Its basic idea is to decompose a given problem into two or more similar, but simpler, subproblems, to solve them in turn, and to compose their solutions to solve the given problem. Problems of sufficient simplicity are solved directly.

   Divide-and-conquer algorithm - Wikipedia

   en.wikipedia.org/wiki/Divide-and-conquer_algorithm

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   How do you divide and conquer a problem?

   • Divide and conquer can be done in three broad steps, divide (into subproblems), conquer (by solving the subproblems), and combine (the answers to solve the original problem). Divide and conquer has a recursive step, where subproblems are solved, and a base case, which is the point where the problem can't be broken down any further.

   Divide and Conquer | Brilliant Math & Science Wiki

   brilliant.org/wiki/divide-and-conquer/

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