de Gruyter Inventory Optimization: Models and Simulations

If you are a reasonably well-learnèd inventory manager who understands basic statistics, Excel, and Python you will adore this book. I use this book as my go-to field manual when designing inventory optimization at work. The two best books on SCM that I have ever found are this book and Vandeput's other book on Data Science for Supply Chain Forecasting. Your IQ does need to be somewhat high to get anything out of this book (if you failed statistics don't bother), but if you have the background and you're passionate about technical things you will eat this up.I highly recommend this if you're an advanced practitioner attempting to do stochastic inventory control for your firm. I highly recommend this for anyone who is in any sort of masters program in SCM too — I would say it's equivalent to roughly 8 semester hours of credits in academia.A final word: if you're into this stuff, please do yourself a favor and get on Linux. WSL on Windows + VSCode editor running WSL remote is where most people should start (if you're a business type locked into Excel). From there you can deploy your stuff on with Docker to cloud for automated compute. Mac probably works too, just stay away from native Windows for the Python ecosystem tools, that's why Microsoft put Linux into Windows so you could have the best of both worlds for prototyping things rapidly.

Very well explained, lot of ideas and formulas. Now only meed to learn Python

Great combination of theory behind models, meaning of various consepts and assistance to easily implement the models in excel and/or python.

Good book with a lot of content. However, more college textbook reading type.The author has well-articulated his knowledge in the book.Overall good book but somewhere delivery style needs more attention to make the reader be engaged in the contents

This is my favorite book of the three books Nicolas published thus far as of Nov 2023. I read it after finishing his other book on "Data science for supply chain forecasting", which really sparked my interest to dive deeper into these topics.Nicolas showcases how to use mathematical models to capture supply chain complexities. With each chapter, the models become more powerful and more capable to capture reality. Finally, simulations are presented as pinnacle of optimization.I had some background in Python so it was really a breeze to implement the suggested code snippets and use them as baseline to develop my own models and simulations. It was a great inspiration. Even if you are not a Python expert, you can use ChatGPT for troubleshooting and coding support!This book can help you to bring your inventory management policies to the next level, leaving outdated approaches such as ABC/XYZ + economical order quantity methods far behind and deploying modern continuous optimization through simulation.For instance, I modeled the total cost of ownership for our company: From purchase order placement through consumption of parts/delivery, factoring in dynamic transaction cost, inventory holding cost and backorder cost as function of order quantity and service level / fill rate. Using probability mass functions for demand and supply lead times based on historical and forecasted data, simulations enabled me to find optimum sets of order parameters and safety stock to operate in the proximity of the total cost minimum - fantastic!Once you grasp the concepts you realize the power this book allows you to harness.