Computational methods in optimization

Generally optimization methods can be classified into general methods and methods tailored for a specific class of problems.
Specific methods such as linear programming and quadratic programming are more efficient than the general methods in solving the problems because they are tailored for it.
The purpose of optimization is to achieve the “best” design relative to a set of prioritized criteria or constraints.

Computing Methods in Optimization Problems deals with hybrid computing methods and optimization techniques using computers. One paper discusses different numerical approaches to optimizing trajectories, including the gradient method, the second variation method, and a generalized Newton-Raphson method.

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