Overview of this book

Simulation modeling helps you to create digital prototypes of physical models to analyze how they work and predict their performance in the real world. With this comprehensive guide, you'll understand various computational statistical simulations using Python. Starting with the fundamentals of simulation modeling, you'll understand concepts such as randomness and explore data generating processes, resampling methods, and bootstrapping techniques. You'll then cover key algorithms such as Monte Carlo simulations and Markov decision processes, which are used to develop numerical simulation models, and discover how they can be used to solve real-world problems. As you advance, you'll develop simulation models to help you get accurate results and enhance decision-making processes. Using optimization techniques, you'll learn to modify the performance of a model to improve results and make optimal use of resources. The book will guide you in creating a digital prototype using practical use cases for financial engineering, prototyping project management to improve planning, and simulating physical phenomena using neural networks. By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.
Preface
Section 1: Getting Started with Numerical Simulation
Free Chapter
Chapter 1: Introducing Simulation Models
Chapter 2: Understanding Randomness and Random Numbers
Chapter 3: Probability and Data Generation Processes
Section 2: Simulation Modeling Algorithms and Techniques
Chapter 4: Exploring Monte Carlo Simulations
Chapter 5: Simulation-Based Markov Decision Processes
Chapter 6: Resampling Methods
Chapter 7: Using Simulation to Improve and Optimize Systems
Section 3: Real-World Applications
Chapter 8: Using Simulation Models for Financial Engineering
Chapter 9: Simulating Physical Phenomena Using Neural Networks
Chapter 10: Modeling and Simulation for Project Management
Chapter 11: What's Next?
Other Books You May Enjoy

Scheduling project time using Monte Carlo simulation

Each project requires a time of realization, and the beginning of some activities can be independent or dependent on previous activities ending. Scheduling a project means determining the times of realization of the project itself. A project is a temporary effort undertaken to create a unique product, service, or result. The term project management refers to the application of knowledge, skills, tools, and techniques for the purpose of planning, managing, and controlling a project and the activities of which it is composed.

The key figure in this area is the project manager, who has the task and responsibility of coordinating and controlling the various components and actors involved, with the aim of reducing the probability of project failure. The main difficulty in this series of activities is to achieve the objectives set in compliance with constraints such as the scope of the project, time, costs, quality, and resources. In...