Description
Book SynopsisMultiple 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.
Table of ContentsMulti-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
