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Mathematical optimization or mathematical programming is the selection of the best element from some set of available alternatives. Optimization problems of sorts 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 simplest case, 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…mehr

Produktbeschreibung
Mathematical optimization or mathematical programming is the selection of the best element from some set of available alternatives. Optimization problems of sorts 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 simplest case, 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.
Autorenporträt
Gaurav Dhiman wurde 1981 in Pathankot, Indien, geboren. Er erhielt 2003 den B.Tech.-Abschluss in Elektronik und Kommunikationstechnik von der Punjab Technical University, Jalandhar, Indien, und 2011 und 2018 den M.Tech.- und Ph.D.-Abschluss in VLSI-Design von der Mody University of Science and Technology (MUST) Lakshmangarh, Rajasthan, Indien.