Book Image

Hands-On Simulation Modeling with Python

By : Giuseppe Ciaburro
Book Image

Hands-On Simulation Modeling with Python

By: Giuseppe Ciaburro

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.
Table of Contents (16 chapters)
Section 1: Getting Started with Numerical Simulation
Section 2: Simulation Modeling Algorithms and Techniques
Section 3: Real-World Applications

Introducing numerical optimization techniques

In real life, optimizing means choosing the best option among several available alternatives. Each of us optimizes an itinerary to reach a destination, organizes our day, how we use savings, and so on. In mathematics, optimizing means determining the value of the variables of a function so that it assumes its minimum or maximum. Optimization is the discipline that deals with the formulation of useful models in applications, thereby using efficient methods to identify an optimal solution.

Optimization models have great practical interest for the many applications offered. In fact, there are numerous decision-making processes that require you to determine the choice that minimizes the cost or maximizes the gain and are therefore attributable to optimization models. In optimization theory, a relevant position is occupied by mathematical optimization models, for which the evaluation function and the constraints that characterize the permissible...