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Hands-on Mathematical Optimization With Python

Hands-on Mathematical Optimization With Python

Paperback (16 Jan 2025)

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Publisher's Synopsis

This practical guide to optimization combines mathematical theory with hands-on coding examples to explore how Python can be used to model problems and obtain the best possible solutions. Presenting a balance of theory and practical applications, it is the ideal resource for upper-undergraduate and graduate students in applied mathematics, data science, business, industrial engineering and operations research, as well as practitioners in related fields. Beginning with an introduction to the concept of optimization, this text presents the key ingredients of an optimization problem and the choices one needs to make when modeling a real-life problem mathematically. Topics covered range from linear and network optimization to convex optimization and optimizations under uncertainty. The book's Python code snippets, alongside more than 50 Jupyter notebooks on the author's GitHub, allow students to put the theory into practice and solve problems inspired by real-life challenges, while numerous exercises sharpen students' understanding of the methods discussed.

About the Publisher

Cambridge University Press

Cambridge University Press dates from 1534 and is part of the University of Cambridge. We further the University's mission by disseminating knowledge in the pursuit of education, learning and research at the highest international levels of excellence.

Book information

ISBN: 9781009493505
Publisher: Cambridge University Press
Imprint: Cambridge University Press
Pub date:
DEWEY: 519.602855133
DEWEY edition: 23
Language: English
Number of pages: 387
Weight: 688g
Height: 178mm
Width: 255mm
Spine width: 30mm