Multiple Criteria Decision Making in Supply Chain Management, Pawlak, Ralph R. (Retired - General Motors, Fisher-Price, and Vibratech, Williamsville, New York, USA)
Описание: This book brings together, in a single volume, the fields of multicriteria decision making and multiobjective optimization that are traditionally covered by different books. It is written in a didactic form using examples to help understanding of the proposed methodologies better.
Описание: This book focuses on the impact of artificial intelligence (AI) and machine learning (ML) models on supply chain operations in industry 4.0. The chapters illustrate the AI and ML models for all functional areas of operations in SCM. The book also includes examples using ML models like handling supply-to-demand imbalances, triggering automated responses, and reinforcing customer relationships. It describes the evolution of blockchain technology coupled with the ability to automate business logic for the transparency of goods, infrastructure, products, and licenses in software. The book also includes case studies that provide a problem statement and industry overcome by applying ML and AI technologies. This book is suitable for undergraduates, postgraduates, industrial professionals, business executives, entrepreneurs, and freelancers to encourage practical learning on AI and ML algorithms in SCM 4.0. Additionally, this book will provide computer science and information system professionals with the latest technologies embedded in the corporate world.
Описание: This book focuses on the impact of artificial intelligence (AI) and machine learning (ML) models on supply chain operations in industry 4.0. The chapters illustrate the AI and ML models for all functional areas of operations in SCM. The book also includes examples using ML models like handling supply-to-demand imbalances, triggering automated responses, and reinforcing customer relationships. It describes the evolution of blockchain technology coupled with the ability to automate business logic for the transparency of goods, infrastructure, products, and licenses in software. The book also includes case studies that provide a problem statement and industry overcome by applying ML and AI technologies. This book is suitable for undergraduates, postgraduates, industrial professionals, business executives, entrepreneurs, and freelancers to encourage practical learning on AI and ML algorithms in SCM 4.0. Additionally, this book will provide computer science and information system professionals with the latest technologies embedded in the corporate world.
Автор: Hans-Otto G?nther; Herbert Meyr Название: Supply Chain Planning ISBN: 3642100988 ISBN-13(EAN): 9783642100987 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses decision-making activities in supply chain management at the strategic, tactical and operational levels. The primary focus is on the application of quantitative methods, and it includes recent research results on collaborative planning.
Автор: Teresa Wu; Jennifer Vincent Blackhurst Название: Managing Supply Chain Risk and Vulnerability ISBN: 1447157834 ISBN-13(EAN): 9781447157830 Издательство: Springer Рейтинг: Цена: 19589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Effective supply chain management is crucial to a company`s ability to fill consumer demand, regardless of the industry. This book presents topics on the assessment, modeling and monitoring of supply chain risk.
Автор: Cengiz Kahraman; ?rem Otay Название: Fuzzy Multi-criteria Decision-Making Using Neutrosophic Sets ISBN: 3030000443 ISBN-13(EAN): 9783030000448 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a comprehensive guide to the use of neutrosophic sets in multiple criteria decision making problems. It shows how neutrosophic sets, which have been developed as an extension of fuzzy and paraconsistent logic, can help in dealing with certain types of uncertainty that classical methods could not cope with. The chapters, written by well-known researchers, report on cutting-edge methodologies they have been developing and testing on a variety of engineering problems. The book is unique in its kind as it reports for the first time and in a comprehensive manner on the joint use of neutrosophic sets together with existing decision making methods to solve multi-criteria decision-making problems, as well as other engineering problems that are complex, hard to model and/or include incomplete and vague data. By providing new ideas, suggestions and directions for the solution of complex problems in engineering and decision making, it represents an excellent guide for researchers, lecturers and postgraduate students pursuing research on neutrosophic decision making, and more in general in the area of industrial and management engineering.
Автор: Xu Jiuping, Tao Zhimiao Название: Rough Multiple Objective Decision Making ISBN: 143987235X ISBN-13(EAN): 9781439872352 Издательство: Taylor&Francis Рейтинг: Цена: 31390.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Under intense scrutiny for the last few decades, Multiple Objective Decision Making (MODM) has been useful for dealing with the multiple-criteria decisions and planning problems associated with many important applications in fields including management science, engineering design, and transportation. Rough set theory has also proved to be an effective mathematical tool to counter the vague description of objects in fields such as artificial intelligence, expert systems, civil engineering, medical data analysis, data mining, pattern recognition, and decision theory.
Rough Multiple Objective Decision Making is perhaps the first book to combine state-of-the-art application of rough set theory, rough approximation techniques, and MODM. It illustrates traditional techniques--and some that employ simulation-based intelligent algorithms--to solve a wide range of realistic problems. Application of rough theory can remedy two types of uncertainty (randomness and fuzziness) which present significant drawbacks to existing decision-making methods, so the authors illustrate the use of rough sets to approximate the feasible set, and they explore use of rough intervals to demonstrate relative coefficients and parameters involved in bi-level MODM. The book reviews relevant literature and introduces models for both random and fuzzy rough MODM, applying proposed models and algorithms to problem solutions.
Given the broad range of uses for decision making, the authors offer background and guidance for rough approximation to real-world problems, with case studies that focus on engineering applications, including construction site layout planning, water resource allocation, and resource-constrained project scheduling. The text presents a general framework of rough MODM, including basic theory, models, and algorithms, as well as a proposed methodological system and discussion of future research.
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