Big data analytics in supply chain management, Iman Rahimi, Amir H. Gandomi, Simon James Fong
Автор: Holdaway Keith Название: Harness Oil and Gas Big Data with Analytics ISBN: 1118779312 ISBN-13(EAN): 9781118779316 Издательство: Wiley Рейтинг: Цена: 9108.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Use big data analytics to efficiently drive oil and gas exploration and production Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry.
Автор: Heckmann Название: Towards Supply Chain Risk Analytics ISBN: 3658148691 ISBN-13(EAN): 9783658148690 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this thesis, Iris Heckmann develops a profound conceptual basis of supply chain risk analytics. She transfers the newly defined concepts for the modelling and operationalization of supply chain risk within simulation and optimization approaches, in order to ease unexpected deviations and disruptions, which are subsumed under the notion of supply chain risk, increasingly aggravating the planning and optimization of supply chains.
Автор: Deep Название: Logistics, Supply Chain and Financial Predictive Analytics ISBN: 9811308713 ISBN-13(EAN): 9789811308710 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: and determining initial, basic and feasible solutions for transportation problems by means of the "supply demand reparation method" and "continuous allocation method." In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices;
Описание: Learn from research into smart, integrated and sustainable logistics practices, with a focus on market requirements and cutting edge applications from innovators in the logistics industry.
Описание: Harness data within the supply chain using this accessible guide on how to examine, evaluate and apply business analytics models.
Автор: Kusum Deep; Madhu Jain; Said Salhi Название: Logistics, Supply Chain and Financial Predictive Analytics ISBN: 9811345228 ISBN-13(EAN): 9789811345227 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses a broad range of problems commonly encountered in the fields of financial analysis, logistics and supply chain management, such as the use of big data analytics in the banking sector. Divided into twenty chapters, some of the contemporary topics discussed in the book are co-operative/non-cooperative supply chain models for imperfect quality items with trade-credit financing; a non-dominated sorting water cycle algorithm for the cardinality constrained portfolio problem; and determining initial, basic and feasible solutions for transportation problems by means of the “supply demand reparation method” and “continuous allocation method.” In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices; optimal policy for Weibull distributed deteriorating items varying with ramp type demand rate and shortages; an inventory model with shortages and deterioration for three different demand rates; outlier labeling methods for medical data; a garbage disposal plant as a validated model of a fault-tolerant system; and the design of a “least cost ration formulation application for cattle”; a preservation technology model for deteriorating items with advertisement dependent demand and trade credit; a time series model for stock price forecasting in India; and asset pricing using capital market curves.The book offers a valuable asset for all researchers and industry practitioners working in these areas, giving them a feel for the latest developments and encouraging them to pursue further research in this direction.
Автор: Robertson, Peter W. Название: Supply chain analytics ISBN: 0367540061 ISBN-13(EAN): 9780367540067 Издательство: Taylor&Francis Рейтинг: Цена: 7195.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces the reader to data analytics and demonstrates the value of their effective use in supply chain management. By describing the key Supply Chain processes through worked examples, and the methods that can be applied to improve those processes, the book presents a comprehensive learning experience.
Автор: Matthew Liberatore, Tan Miller Название: Supply Chain Planning: An Analytics-based Approach ISBN: 195334920X ISBN-13(EAN): 9781953349200 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 4012.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The critical role that supply chain planning contributes to a firm’s financial well-being has never been greater. All too often, however, considerable managerial resources are directed toward planning activities with minimal results. In this book, we present proven, practical management frameworks used by the authors to support supply chain operations management and planning in private industry. These frameworks provide methodologies for managing critical activities such as supply chain strategic planning and project selection, manufacturing and distribution planning, performance measurement, supply chain risk management, and customer logistics and inventory deployment. The book is intended for supply chain professionals, as well as for graduate and advanced undergraduate students. Practitioners will obtain valuable new insights and examples of implementable frameworks and methods for managing their supply chain functions and organizations. Students will develop an understanding of real-world approaches for supply chain planning, decision support, and many other key activities.
Автор: Chan Hing Kai, Subramanian Nachiappan, Abdulrahman Muhammad Dan-Asabe Название: Supply Chain Management in the Big Data Era ISBN: 1522509569 ISBN-13(EAN): 9781522509561 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28413.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Technological advancements in recent years have led to significant developments within a variety of business applications. In particular, data-driven research provides ample opportunity for enterprise growth, if utilized efficiently.Supply Chain Management in the Big Data Era is an authoritative reference source for the latest scholarly material on the implementation of big data analytics for improved operations and supply chain processes. Highlighting emerging strategies from different industry perspectives, this book is ideally designed for managers, professionals, practitioners, and students interested in the most recent research on supply chain innovations.
Автор: Patrik Jonsson Название: Logistics and Supply Chain Management ISBN: 0077117387 ISBN-13(EAN): 9780077117382 Издательство: McGraw-Hill Рейтинг: Цена: 9779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Helps student understand the `game rules` goals and objectives when designing, planning and controlling efficient and effective logistics systems in supply chains. This book covers information technology, and the impact of manufacturing and product structures on logistics and supply chain systems, and the environment.
Автор: Wong Название: Big Data Analytics in Genomics ISBN: 3319412787 ISBN-13(EAN): 9783319412788 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field.
This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA. In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science. Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.
Автор: Pyne Название: Big Data Analytics ISBN: 8132236262 ISBN-13(EAN): 9788132236269 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.
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