Introduction: Overview of Unconstrained Optimization

Neculai Andrei ()
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Neculai Andrei: Academy of Romanian Scientists

Chapter Chapter 1 in Nonlinear Conjugate Gradient Methods for Unconstrained Optimization, 2020, pp 1-66 from Springer

Abstract: Abstract Unconstrained optimization consists of minimizing a function which depends on a number of real variables without any restrictions on the values of these variables. When the number of variables is large, this problem becomes quite challenging. The most important gradient methods for solving unconstrained optimization problems are described in this chapter. These methods are iterative.

Date: 2020
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DOI: 10.1007/978-3-030-42950-8_1

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