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https://doi.org/10.4995/mr.202...
Book . 2024 . Peer-reviewed
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Notebooks for Operations Research. A practical guide to operations research with Python

Authors: Francisco Fraile Gil;

Notebooks for Operations Research. A practical guide to operations research with Python

Abstract

Notebooks for Operations Research is a practical guide that uses Python and Jupyter Notebooks to teach the principles and applications of operations research. Designed for both beginning students and professionals, the text connects theory and practice through interactive tutorials, solved exercises, and the use of Python libraries to solve problems with a hands-on approach. Chapters cover topics such as linear programming, combinatorial optimisation, non-linear programming, decision and game theory, simulation and Markov chains. Each section integrates mathematical concepts with real-world applications, demonstrating how to solve optimisation and decision-making problems in complex contexts, especially in supply chain management. In addition, the book highlights the relationship between operations research and artificial intelligence, focusing on mathematical reasoning and optimisation techniques, and provides an introduction to machine learning. It is an interactive book in the sense that all content is available in an interactive online environment that allows experimentation with the code. It provides fundamentals, tools and open source resources for those seeking to master operations research in a practical and modern approach.

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Spain
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Keywords

OPERACIÓN LINEAL, OPTIMIZACIÓN, Organización, thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management, INVESTIGACIÓN OPERATIVA, Economía, Empresa

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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