Big Data Analytics Using Multiple Criteria Decision-Making Models Operations Research Series

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.

Multi-Criteria Leadership and Decisions: Festschrift in Honor of Ravi Ravindran; Multi-Criteria Decision Making: An Overview and a Comparative Discussion; Basics of Analytics and Big Data; Linear-Programming (LP)-Based Two Phase Classifier for Solving a Classification Problem with Multiple Objectives; Multi-Criteria Evaluation of Predictive Analytics for Electric Utility Service Management; Multi-Objective Forecasting: Time Series Models using a Deterministic Pseudo- Evolutionary Algorithm; A Class of Models for Micro-Grid Optimization; A Data-Driven Approach for Multi-Objective Loan Portfolio Optimization using Machine Learning Algorithms and Mathematical Programming; Multi-Objective Routing in a Metropolitan City with Deterministic and Dynamic Travel and Waiting Times, and One-Way Traffic Regulation; Designing Resilient Global Supply Chain Networks over Multiple Time Periods within Complex International Environments; An MCDM based Modeling Framework for Continuous Performance Evaluation of Employees to Offer Reward and Recognition; The use of DEA for studying the link between environmental and manufacturing performance; An Integrated Multi Criteria Decision Making Model for New Product Portfolio Management

RAMAKRISHNAN RAMANATHAN

Professor Ram Ramanathan is the Director of Business and Management Research Institute, in the Business School of the University of Bedfordshire, Luton, UK. In the past, he has worked and taught in a number of countries, including the UK, Finland, the Netherlands, Oman and India. He has taught basic and advanced courses on Operations Management, Production Systems Management, Supply Chain Management, Optimization Theory, Data Envelopment Analysis (DEA), Management Science, Business Statistics, Simulation, Energy and Environment, Energy and Environmental Economics, Energy and Transport Economics, and others. His research interests include operations management, supply chains, environmental sustainability, economic and policy analysis of issues in the energy, environment, transport and other infrastructure sectors. He works extensively on modelling using techniques such as optimisation, decision analysis, data envelopment analysis and the analytic hierarchy process.

Ram has successfully completed a number of research projects across the world. He is on the editorial boards of several journals and in the technical/advisory committees of several international conferences in his field. He is an advisory board member of an innovative new online resource, The Oxford Research Encyclopedia of Business and Management. He is a member of ESRC Peer Review College in the UK. He has produced four books (including an introductory textbook on DEA), more than 119 research publications in journals and more than 141 conference presentations. His research articles have appeared in many prestigious internationally refereed journals including Omega, Tourism Economics, International Journal of Production Economics, Supply Chain Management, International Journal of Operations & Production Management, European Journal of Operational Research, Transport Policy, and, Transportation Research.

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