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Specific applications of search algorithms include: Problems in combinatorial optimization, such as: . The vehicle routing problem, a form of shortest path problem; The knapsack problem: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as ...
Every search problem also has a corresponding decision problem, namely L ( R ) = { x ∣ ∃ y R ( x , y ) } . {\displaystyle L(R)=\{x\mid \exists yR(x,y)\}.\,} This definition may be generalized to n -ary relations using any suitable encoding which allows multiple strings to be compressed into one string (for instance by listing them ...
A simple and inefficient way to see where one string occurs inside another is to check at each index, one by one. First, we see if there is a copy of the needle starting at the first character of the haystack; if not, we look to see if there's a copy of the needle starting at the second character of the haystack, and so forth.
Another example of heuristic making an algorithm faster occurs in certain search problems. Initially, the heuristic tries every possibility at each step, like the full-space search algorithm. But it can stop the search at any time if the current possibility is already worse than the best solution already found.
A word search, word find, word seek, word sleuth or mystery word puzzle is a word game that consists of the letters of words placed in a grid, which usually has a rectangular or square shape. The objective of this puzzle is to find and mark all the words hidden inside the box.
For example, a counting problem associated with factoring is "Given a positive integer n, count the number of nontrivial prime factors of n." A counting problem can be represented by a function f from {0, 1} * to the nonnegative integers. For a search relation R, the counting problem associated to R is the function f R (x) = |{y: R(x, y) }|.
Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) to a given point. Closeness is typically expressed in terms of a dissimilarity function: the less similar the objects, the larger the function values.
MAJC (Microprocessor Architecture for Java Computing) was a Sun Microsystems multi-core, multithreaded, very long instruction word (VLIW) microprocessor design from the mid-to-late 1990s. Originally called the UltraJava processor, the MAJC processor was targeted at running Java programs, whose "late compiling" allowed Sun to make several ...