1. (1) Wayne L Winston. Operations Research: Applications and Algorithms (Latest Edition). Duxbury Press. An Imprint of Wadsworth Publishing Company, Belmont, California, USA
   (2) Anderson, Sweeney and Williams. An Introduction to management Science: Quantitative Approaches to Decision Making (Latest Edition). South-Western College Publishing.
   (3) U Dinesh Kumar. Business Analytics: The Science of Data-Driven Decision Making. Wiley India, 2017
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To provide business practitioners and those who are interested in Prescriptive Analytics with a selected set of Management Science and optimization techniques and discuss the fundamental concepts, methods, and models needed to understand prescriptive-analytics and implement these techniques in the era of Big Data.

BE/BTech, ME/MTech, Masters in – Business Administration, Management, Operations Research, Computer Science, Computer Applications, Mathematics, Statistics, Commerce, Economics.

Introduction to Business Analytics, Linear/Integer/Non-Linear Optimization, Optimization of Network Models, Dynamic Programming, Introdcution to Heuristic Programming, Goal Programming, Selected Multi-Attribute Decision Making Methods, and Monte Carlo Simulation, which are believed to be among the most popular Prescriptive Analytics tools to solve a majority of business optimization problems, with case studies from Business, Industry, and Government applications using LINDO/LINGO/CPLEX/Pulb optimization package(s).