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.
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.
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.
Inhaltsangabe
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
