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Download as PDF; Printable version; In other projects ... Divide-and-conquer algorithm; C. ... Text is available under the Creative Commons Attribution-ShareAlike 4.0 ...
Defeat in detail, or divide and conquer, is a military tactic of bringing a large portion of one's own force to bear on small enemy units in sequence, rather than engaging the bulk of the enemy force all at once. This exposes one's own units to many small risks but allows for the eventual destruction of an entire enemy force.
Similar to divide and conquer; Denial – A strategy that seeks to destroy the enemy's ability to wage war; Distraction – An attack by some of the force on one or two flanks, drawing up to a strong frontal attack by the rest of the force; Encirclement – Both a strategy and tactic designed to isolate and surround enemy forces
Its primary application is the approximation of the running time of many divide-and-conquer algorithms. For example, in the merge sort , the number of comparisons required in the worst case, which is roughly proportional to its runtime, is given recursively as T ( 1 ) = 0 {\displaystyle T(1)=0} and
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.
The Schönhage–Strassen algorithm was the asymptotically fastest multiplication method known from 1971 until 2007. It is asymptotically faster than older methods such as Karatsuba and Toom–Cook multiplication, and starts to outperform them in practice for numbers beyond about 10,000 to 100,000 decimal digits. [2]
It is a specific type of divide and conquer algorithm. A well-known example is binary search. [3] Abstractly, a dichotomic search can be viewed as following edges of an implicit binary tree structure until it reaches a leaf (a goal or final state).
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