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Hands-On Simulation Modeling with Python

You're reading from   Hands-On Simulation Modeling with Python Develop simulation models to get accurate results and enhance decision-making processes

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781838985097
Length 346 pages
Edition 1st Edition
Languages
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Author (1):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Getting Started with Numerical Simulation
2. Chapter 1: Introducing Simulation Models FREE CHAPTER 3. Chapter 2: Understanding Randomness and Random Numbers 4. Chapter 3: Probability and Data Generation Processes 5. Section 2: Simulation Modeling Algorithms and Techniques
6. Chapter 4: Exploring Monte Carlo Simulations 7. Chapter 5: Simulation-Based Markov Decision Processes 8. Chapter 6: Resampling Methods 9. Chapter 7: Using Simulation to Improve and Optimize Systems 10. Section 3: Real-World Applications
11. Chapter 8: Using Simulation Models for Financial Engineering 12. Chapter 9: Simulating Physical Phenomena Using Neural Networks 13. Chapter 10: Modeling and Simulation for Project Management 14. Chapter 11: What's Next? 15. Other Books You May Enjoy

Chapter 7: Using Simulation to Improve and Optimize Systems

Simulation models allow us to obtain a lot of information using few resources. As often happens in life, simulation models are also subject to improvements in order to increase their performance. Through optimization techniques, we try to modify the performance of a model to obtain improvements both in terms of the results and when trying to exploit resources. Optimization problems are usually so complex that a solution cannot be determined analytically. Complexity is determined first by the number of variables and constraints, which define the size of the problem, and then by the possible presence of non-linear functions. To solve an optimization problem, it is necessary to use an iterative algorithm that, given a current approximation of the solution, determines, with an appropriate sequence of operations, updates to this approximation. Starting from an initial approximation, a sequence of approximations that progressively...

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