Operations Research And Big Data

This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.

This book provides a holistic overview of the major advances that have been made in the context of Service Science with a focus on IT-enabled services. To address challenges in collaborative, social-centric, ad-hoc, dynamic and open environments, the book studies IT-enabled service systems from two distinct but complementary research perspectives: service engineering and service computing. From a service engineering view, the book shows how to apply a systemic approach to tackle social problems from holistic and multi-disciplinary perspectives by focusing on service systems and developing a service design framework, including socio-technical aspects, the service reference model, data-driven collaboration processes, the incremental design method, requirement propagation, and system adaptability with feedback loops. From a service computing view, the book introduces a service-oriented aided infrastructure to support IT-enabled service systems in ICT-facilitated environments and provide access to tangible and intangible resources in a trustworthy environment.

This book presents selected papers from the 4th Conference of the Transportation Research Group of India. It provides a comprehensive analysis of themes spanning the field of transportation encompassing economics, financial management, social equity, green technologies, operations research, big data analysis, econometrics and structural mechanics. This volume will be of interest to researchers, educators, practitioners, managers, and policy-makers world-wide.

This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.