Название: An Introduction to Mathematical Programming and Network Science: Examples with Theory and Python
Автор: Nathan Grieve
Издательство: Springer
Серия: Springer Undergraduate Texts in Mathematics and Technology
Год: 2026
Страниц: 330
Язык: английский
Формат: pdf (true), epub
Размер: 31.4 MB
This text provides a practical, hands-on introduction to the fundamental concepts of mathematical programming and network science. Particular emphasis is placed on linear programming, mathematical modelling and case studies, the implementation of the Simplex Method in Python, and classical techniques from nonlinear convex programming. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Designed as an introductory resource for upper-level undergraduate and graduate students, the book assumes only a modest mathematical background. Readers who have completed a second course in linear algebra, multivariable calculus, and an introductory course in probability and statistics will find the more advanced portions of the text especially accessible. Researchers and professionals in mathematics, engineering, technology, economics, business, and other quantitatively oriented fields will also find this book a valuable reference.