Operations Research and Big Data

by Ana Paula Ferreira Dias Barbosa Póvoa
Operations Research and Big Data
Author: Ana Paula Ferreira Dias Barbosa Póvoa
Publisher: Springer
Total Pages: 255
Release: 2015-09-11
Genre: Technology & Engineering
ISBN: 3319241540
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The development of Operations Research (OR) requires constant improvements, such as the integration of research results with business applications and innovative educational practice. The full deployment and commercial exploitation of goods and services generally need the construction of strong synergies between educational institutions and businesses. The IO2015 -XVII Congress of APDIO aims at strengthening the knowledge triangle in education, research and innovation, in order to maximize the contribution of OR for sustainable growth, the promoting of a knowledge-based economy, and the smart use of finite resources. The IO2015-XVII Congress of APDIO is a privileged meeting point for the promotion and dissemination of OR and related disciplines, through the exchange of ideas among teachers, researchers, students , and professionals with different background, but all sharing a common desire that is the development of OR.

Applied Big Data Analytics in Operations Management

by Kumar, Manish
Applied Big Data Analytics in Operations Management
Author: Kumar, Manish
Publisher: IGI Global
Total Pages: 270
Release: 2016-09-30
Genre: Business & Economics
ISBN: 1522508872
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Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.

Big Data Analytics in Supply Chain Management

by Iman Rahimi
Big Data Analytics in Supply Chain Management
Author: Iman Rahimi
Publisher: CRC Press
Total Pages: 211
Release: 2020-12-20
Genre: Computers
ISBN: 1000326918
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In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.

Data-Enabled Analytics

by Joe Zhu
Data-Enabled Analytics
Author: Joe Zhu
Publisher: Springer Nature
Total Pages: 370
Release: 2021-12-16
Genre: Business & Economics
ISBN: 3030751627
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This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.

Operations Research and Enterprise Systems

by Greg H. Parlier
Operations Research and Enterprise Systems
Author: Greg H. Parlier
Publisher: Springer
Total Pages: 254
Release: 2019-03-14
Genre: Computers
ISBN: 3030160351
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This book constitutes revised selected papers from the 7th International Conference on Operations Research and Enterprise Systems, ICORES 2018, held in Funchal, Madeira, Portugal, in January 2018. The 12 papers presented in this volume were carefully reviewed and selected from a total of 59 submissions. They are organized in topical sections named: methodologies and technologies; and applications.

Big Data Analytics Using Multiple Criteria Decision-Making Models

by Ramakrishnan Ramanathan
Big Data Analytics Using Multiple Criteria Decision-Making Models
Author: Ramakrishnan Ramanathan
Publisher: CRC Press
Total Pages: 435
Release: 2017-07-12
Genre: Computers
ISBN: 1351648691
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Multiple Criteria Decision Making (MCDM) is a subfield of Operations Research, dealing with decision making problems. A decision-making problem is characterized by the need to choose one or a few among a number of alternatives. The field of MCDM assumes special importance in this era of Big Data and Business Analytics. In this volume, the focus will be on modelling-based tools for Business Analytics (BA), with exclusive focus on the sub-field of MCDM within the domain of operations research. The book will include an Introduction to Big Data and Business Analytics, and challenges and opportunities for developing MCDM models in the era of Big Data.

Big Data Management

by Fausto Pedro García Márquez
Big Data Management
Author: Fausto Pedro García Márquez
Publisher: Springer
Total Pages: 274
Release: 2016-11-15
Genre: Computers
ISBN: 3319454986
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This book focuses on the analytic principles of business practice and big data. Specifically, it provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management, serving as a complement to books in other disciplines such as economics, finance, marketing and risk analysis. The contributors present their areas of expertise, together with essential case studies that illustrate the successful application of engineering management theories in real-life examples.

Big Data Meets Survey Science

by Craig A. Hill
Big Data Meets Survey Science
Author: Craig A. Hill
Publisher: John Wiley & Sons
Total Pages: 784
Release: 2020-09-29
Genre: Social Science
ISBN: 1118976320
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Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.

Big Data Optimization: Recent Developments and Challenges

by Ali Emrouznejad
Big Data Optimization: Recent Developments and Challenges
Author: Ali Emrouznejad
Publisher: Springer
Total Pages: 492
Release: 2016-05-26
Genre: Technology & Engineering
ISBN: 3319302655
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The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.