Introduction to Mathematical Models in Operations Planning

Discover the intricate nature of a company's production function and the comprehensive principles of planning operations in this book. Through practical applications and enriched by numerical examples, readers gain essential knowledge of elementary mathematical methods in operations planning. The inclusion of the powerful R programming language, accompanied by code scripts and real-world examples, enhances the learning experience. Blending theory with practice, this resource equips readers with the tools necessary to optimize production systems, make informed decisions, and gain a competitive edge in today's dynamic business landscape.

List of contents

Preface

CHAPTER 1: Introduction
CHAPTER 2: Operations planning
CHAPTER 3: Manufacturing processes
CHAPTER 4: Facility layout and line balancing
CHAPTER 5: Project scheduling
CHAPTER 6: Work center scheduling
CHAPTER 7: Linear programming in operations planning
CHAPTER 8: Aggregate operations planning
REFERENCES

About the author

Halit Alper Tayal¿ is an assistant professor of business with expertise in enhancing productivity and efficiency. As a co-editor of Istanbul Business Research, an ESCI-indexed journal, his commitment to advancing research and knowledge in the field is evident. With a solid academic background, including studies at Istanbul American Robert College, Koç University, and ESC Rennes, he has practical experience through involvement in his family business. His entrepreneurial spirit led him to co-found a software development startup with support from the Scientific and Technological Research Council of Türkiye, highlighting his dedication to innovation and practical applications. As his academic journey continues at Istanbul University, he empowers individuals in the realm of production planning and beyond, driving progress and excellence.

Summary

This book aims to provide the readers with methodologies, and reviews trends and issues in forecasting in production planning. Furthermore, it presents machine learning methods used in time series forecasting.

Product details

• Authors: Halit Alper (Istanbul Universitesi) Tayal, Halit Alper Tayali, Halit Alper (Istanbul Universitesi) Tayali, Halit Alper Tayalı
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 30.10.2023
• EAN: 9781032191997
• ISBN: 978-1-0-3219199-7
• No. of pages: 116
• Subjects: Social sciences, law, business > Business > General, dictionaries; SCIENCE / Life Sciences / General, Artificial Intelligence, BUSINESS & ECONOMICS / Economics / General, MATHEMATICS / Probability & Statistics / General, BUSINESS & ECONOMICS / Production & Operations Management, Economic statistics, Probability & statistics, Purchasing & supply management, Production & quality control management, Probability and statistics, Econometrics and economic statistics, Network Management, Production and quality control management, Purchasing and supply management