Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

© Robert Johansson 2019

Robert JohanssonNumerical Python https://doi.org/10.1007/978-1-4842-4246-9_6

6. Optimization

Robert Johansson¹ 

(1)

Urayasu-shi, Chiba, Japan

 

In this chapter, we will build on Chapter 5 about equation solving and explore the related topic of solving optimization problems. In general, optimization is the process of finding and selecting the optimal element from a set of feasible candidates. In mathematical optimization, this problem is usually formulated as determining the extreme value of a function on a given domain. An extreme value, or an optimal value, can refer to either the minimum or maximum of the function, depending on the application and the specific problem. In this chapter we are concerned with the optimization ...