Book contents
- Insight-Driven Problem Solving
- Insight-Driven Problem Solving
- Copyright page
- Dedication
- Contents
- Preface
- Introduction
- 1 The Big Picture of Analytics Science
- 2 Artificial Intelligence and Machine Learning
- 3 Queueing Theory and Resource Allocation
- 4 Game Theory and Mechanism Design
- 5 Linear and Nonlinear Mathematical Programming
- 6 Dynamic Programming and Sequential Decision-Making
- 7 Data Analysis
- 8 Graph Theory, Combinatorial Optimization, and Supply Chains
- Acknowledgments
- Notes
- References
- Index
5 - Linear and Nonlinear Mathematical Programming
Published online by Cambridge University Press: 21 October 2025
Book contents
- Insight-Driven Problem Solving
- Insight-Driven Problem Solving
- Copyright page
- Dedication
- Contents
- Preface
- Introduction
- 1 The Big Picture of Analytics Science
- 2 Artificial Intelligence and Machine Learning
- 3 Queueing Theory and Resource Allocation
- 4 Game Theory and Mechanism Design
- 5 Linear and Nonlinear Mathematical Programming
- 6 Dynamic Programming and Sequential Decision-Making
- 7 Data Analysis
- 8 Graph Theory, Combinatorial Optimization, and Supply Chains
- Acknowledgments
- Notes
- References
- Index
Summary
This chapter presents mathematical programming as the science of one-shot decisions. It clarifies important ways analytics scientists implement problem solving by benefiting from tools and ideas in mathematical programming both in scenarios where the world behaves linearly and where it does not. It also introduces integer programming and inverse optimization, showcasing how the main ideas and insights obtained from mathematical programming have been applied to various impactful problems ranging from designing effective diets to allowing the military to improve the efficiency of its operations to make bike sharing systems more accessible.
Keywords
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- Insight-Driven Problem SolvingAnalytics Science to Improve the World, pp. 167 - 187Publisher: Cambridge University PressPrint publication year: 2025
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