optimization algorithm - определение. Что такое optimization algorithm
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Что (кто) такое optimization algorithm - определение

STUDY OF MATHEMATICAL ALGORITHMS FOR OPTIMIZATION PROBLEMS
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Spiral optimization algorithm         
OPTIMIZATION ALGORITHM
Spiral Optimization algorithm
In mathematics, the spiral optimization (SPO) algorithm is a metaheuristic inspired by spiral phenomena in nature.
Brain storm optimization algorithm         
Brain storm optimization
The brain storm optimization algorithm is a heuristic algorithm that focuses on solving multi-modal problems, such as radio antennas design worked on by Yahya Rahmat-Samii, inspired by the brainstorming process, proposed by Dr. Yuhui Shi.
Quantum optimization algorithms         
OPTIMIZATION ALGORITHMS USING QUANTUM COMPUTING
User:Danawr/sandbox/QuantumOptimization; Quantum Optimization; Quantum least squares fitting; Quantum semidefinite programming; Quantum combinatorial optimization; Quantum data fitting; Combinatorial optimization using quantum algorithms; Quantum approximate optimization algorithm
Quantum optimization algorithms are quantum algorithms that are used to solve optimization problems. Mathematical optimization deals with finding the best solution to a problem (according to some criteria) from a set of possible solutions.

Википедия

Mathematical optimization

Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries.

In the more general approach, an optimization problem consists of maximizing or minimizing a real function by systematically choosing input values from within an allowed set and computing the value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics. More generally, optimization includes finding "best available" values of some objective function given a defined domain (or input), including a variety of different types of objective functions and different types of domains.