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Query optimization is a feature of many relational database management systems and other databases such as NoSQL and graph databases.The query optimizer attempts to determine the most efficient way to execute a given query by considering the possible query plans.
Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously.
In terms of mathematical optimization, dynamic programming usually refers to simplifying a decision by breaking it down into a sequence of decision steps over time. This is done by defining a sequence of value functions V 1 , V 2 , ..., V n taking y as an argument representing the state of the system at times i from 1 to n .
Golden-section search conceptually resembles PS in its narrowing of the search range, only for single-dimensional search spaces.; Nelder–Mead method aka. the simplex method conceptually resembles PS in its narrowing of the search range for multi-dimensional search spaces but does so by maintaining n + 1 points for n-dimensional search spaces, whereas PS methods computes 2n + 1 points (the ...
In mathematical optimization and computer science, heuristic (from Greek εὑρίσκω "I find, discover" [1]) is a technique designed for problem solving more quickly when classic methods are too slow for finding an exact or approximate solution, or when classic methods fail to find any exact solution in a search space.
The basic algorithm – greedy search – works as follows: search starts from an enter-point vertex by computing the distances from the query q to each vertex of its neighborhood {: (,)}, and then finds a vertex with the minimal distance value. If the distance value between the query and the selected vertex is smaller than the one between the ...
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 ...
In compiler theory, common subexpression elimination (CSE) is a compiler optimization that searches for instances of identical expressions (i.e., they all evaluate to the same value), and analyzes whether it is worthwhile replacing them with a single variable holding the computed value. [1]