Download or read book Operations Research and Big Data written by Ana Paula Ferreira Dias Barbosa Póvoa and published by Springer. This book was released on 2015-09-11 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Data Analytics Computational Statistics and Operations Research for Engineers written by Debabrata Samanta and published by CRC Press. This book was released on 2022-04-05 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.
Download or read book Big Data Analytics in Supply Chain Management written by Iman Rahimi and published by CRC Press. This book was released on 2020-12-20 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Big Data Analytics Using Multiple Criteria Decision Making Models written by Ramakrishnan Ramanathan and published by CRC Press. This book was released on 2017-07-12 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Data Enabled Analytics written by Joe Zhu and published by Springer Nature. This book was released on 2021-12-16 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Applied Big Data Analytics in Operations Management written by Kumar, Manish and published by IGI Global. This book was released on 2016-09-30 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Big Data Management written by Fausto Pedro García Márquez and published by Springer. This book was released on 2016-11-15 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Big Data and Blockchain for Service Operations Management written by Ali Emrouznejad and published by Springer Nature. This book was released on 2022-02-12 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to provide the necessary background to work with big data blockchain by introducing some novel applications in service operations for both academics and interested practitioners, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book intends to cover theory, research, development, and applications of big data and blockchain, as embedded in the fields of mathematics, engineering, computer science, physics, economics, business, management, and life sciences, to help service operations management.
Download or read book Big Data Optimization Recent Developments and Challenges written by Ali Emrouznejad and published by Springer. This book was released on 2016-05-26 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Behavioral Operational Research written by Martin Kunc and published by Springer. This book was released on 2016-06-29 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Behavioral research is making a significant impact on many academic disciplines. Its status as the source of some of the most profound research in the social sciences is unparalleled. Therefore, it is not surprising that interest in Behavior and Operational Research (OR) is burgeoning, even though understanding the relationship between knowledge, behavior and action has been an academic preoccupation in OR since the beginning of the discipline. This book introduces the idea of Behavioral OR, where the theoretical and empirical developments in the behavioral field are making an impression on OR academics and practitioners alike. The book provides a much needed overview that connects together theory, methodology and practice and offers the “state of the art” on Behavioral Operational Research theory and practice. The book not only includes chapters by leading academics, but also includes rich and insightful real-life case studies by practitioners.
Download or read book Fail Fast Learn Faster written by Randy Bean and published by John Wiley & Sons. This book was released on 2021-08-31 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore why — now more than ever — the world is in a race to become data-driven, and how you can learn from examples of data-driven leadership in an Age of Disruption, Big Data, and AI In Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI, Fortune 1000 strategic advisor, noted author, and distinguished thought leader Randy Bean tells the story of the rise of Big Data and its business impact – its disruptive power, the cultural challenges to becoming data-driven, the importance of data ethics, and the future of data-driven AI. The book looks at the impact of Big Data during a period of explosive information growth, technology advancement, emergence of the Internet and social media, and challenges to accepted notions of data, science, and facts, and asks what it means to become "data-driven." Fail Fast, Learn Faster includes discussions of: The emergence of Big Data and why organizations must become data-driven to survive Why becoming data-driven forces companies to "think different" about their business The state of data in the corporate world today, and the principal challenges Why companies must develop a true "data culture" if they expect to change Examples of companies that are demonstrating data-driven leadership and what we can learn from them Why companies must learn to "fail fast and learn faster" to compete in the years ahead How the Chief Data Officer has been established as a new corporate profession Written for CEOs and Corporate Board Directors, data professional and practitioners at all organizational levels, university executive programs and students entering the data profession, and general readers seeking to understand the Information Age and why data, science, and facts matter in the world in which we live, Fail Fast, Learn Faster p;is essential reading that delivers an urgent message for the business leaders of today and of the future.
Download or read book INFORMS Analytics Body of Knowledge written by James J. Cochran and published by John Wiley & Sons. This book was released on 2018-09-21 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Standardizes the definition and framework of analytics #2 on Book Authority’s list of the Best New Analytics Books to Read in 2019 (January 2019) We all want to make a difference. We all want our work to enrich the world. As analytics professionals, we are fortunate - this is our time! We live in a world of pervasive data and ubiquitous, powerful computation. This convergence has inspired and accelerated the development of both analytic techniques and tools and this potential for analytics to have an impact has been a huge call to action for organizations, universities, and governments. This title from Institute for Operations Research and the Management Sciences (INFORMS) represents the perspectives of some of the most respected experts on analytics. Readers with various backgrounds in analytics – from novices to experienced professionals – will benefit from reading about and implementing the concepts and methods covered here. Peer reviewed chapters provide readers with in-depth insights and a better understanding of the dynamic field of analytics The INFORMS Analytics Body of Knowledge documents the core concepts and skills with which an analytics professional should be familiar; establishes a dynamic resource that will be used by practitioners to increase their understanding of analytics; and, presents instructors with a framework for developing academic courses and programs in analytics.
Download or read book Operations Management and Data Analytics Modelling written by Lalit Kumar Awasthi and published by CRC Press. This book was released on 2021-12-30 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Operations Management and Data Analytics Modelling: Economic Crises Perspective addresses real operation management problems in thrust areas like the healthcare and energy management sectors and Industry 4.0. It discusses recent advances and trends in developing data-driven operation management-based methodologies, big data analysis, application of computers in industrial engineering, optimization techniques, development of decision support systems for industrial operation, the role of a multiple-criteria decision-making (MCDM) approach in operation management, fuzzy set theory-based operation management modelling and Lean Six Sigma. Features Discusses the importance of data analytics in industrial operations to improve economy Provides step-by-step implementation of operation management models to identify best practices Covers in-depth analysis using data-based operation management tools and techniques Discusses mathematical modelling for novel operation management models to solve industrial problems This book is aimed at graduate students and professionals in the field of industrial and production engineering, mechanical engineering and materials science.
Download or read book Data Science and Big Data Computing written by Zaigham Mahmood and published by Springer. This book was released on 2016-07-05 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.
Download or read book Big Data Meets Survey Science written by Craig A. Hill and published by John Wiley & Sons. This book was released on 2020-09-29 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Proceedings of 4th International Conference on BigData Analysis and Data Mining 2017 written by ConferenceSeries and published by ConferenceSeries. This book was released on with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: September 07-08, 2017 Paris, France Key Topics : Cloud computing, Forecasting from Big Data, Optimization and Big Data, New visualization techniques, Social network analysis, Search and data mining, Complexity and Algorithms, Open Data, ETL (Extract, Transform and Load), OLAP Technologies, Big Data Algorithm, Data Mining Analysis, Kernel Methods, Frequent Pattern Mining, Clustering, Data Privacy and Ethics, Big Data Technologies, Business Analytics, Data Mining Methods and Algorithms, Data Mining Tasks and Processes, Data Mining Applications in Science, Engineering, Healthcare and Medicine, Big Data Applications, Data Mining Tools and Software, Data Warehousing, Artificial Intelligence,
Download or read book Operational Research in the Era of Digital Transformation and Business Analytics written by Nikolaos F. Matsatsinis and published by Springer Nature. This book was released on 2023-04-04 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings volume presents new methods and applications in Operational Research and Management Science with a special focus on Business Analytics. Featuring selected contributions from the XIV Balkan Conference on Operational Research held in Thessaloniki, Greece in 2020 (BALCOR 2020), it addresses applications and methodological tools or techniques in various areas of Operational Research, such as agent-based modelling, big data and business analytics, data envelopment analysis, data mining, decision support systems, fuzzy systems, game theory, heuristics, metaheuristics and nature inspired optimization algorithms, linear and nonlinear programming, machine learning, multiple criteria decision analysis, network design and optimization, queuing theory, simulation and statistics.
