Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criteria, from some set of available alternatives. [1][2] It is generally divided into two subfields: discrete optimization and continuous optimization.
The meaning of OPTIMIZATION is an act, process, or methodology of making something (such as a design, system, or decision) as fully perfect, functional, or effective as possible; specifically : the mathematical procedures (such as finding the maximum of a function) involved in this.
In this section we are going to look at optimization problems. In optimization problems we are looking for the largest value or the smallest value that a function can take.
optimization, collection of mathematical principles and methods used for solving quantitative problems in many disciplines, including physics, biology, engineering, economics, and business.
Optimization problem: Maximizing or minimizing some function relative to some set, often representing a range of choices available in a certain situation. The function allows comparison of the different choices for determining which might be “best.”
Price optimization is a data-driven process that uses prescriptive analytics, and advanced optimization software to determine the optimal pricing strategy
optimization, collection of mathematical principles and methods used for solving quantitative problems in many disciplines, including physics, biology, engineering, economics, and business.