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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Halit Alper Tayalı 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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : new. Paperback. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032192017
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Paperback. Etat : new. Paperback. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9781032192017
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Paperback. Etat : new. Paperback. 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. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781032192017
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