Decision Modeling

Decision Modeling is an important component of Operations Research. With the advent of globalization, only those industries survive who would be able make effective decisions. Out of the vast coverage of decision models, this course focuses on decision analysis, waiting line or queuing models, simulation models, and network models. This course will be of immense value not only for the people working in manufacturing or service industry but also to undergraduate and postgraduate students of all fields of engineering and management.INTENDED AUDIENCE: Students from Bachelors in EngineeringMasters in Business AdministrationMasters in EconomicsMasters in Industrial EngineeringMasters in Operations Research/Operations ManagementPhD in related fieldsPREREQUISITES: Basic Probability and StatisticsBasic Operations ResearchINDUSTRY SUPPORT: Manufacturing IndustryChemical IndustryService IndustryManagement Consultancy HousesCorporate Planning Groups

Week 1: Decision Analysis: Introduction to Decision modeling, Probability Concepts, Decision modeling for deterministic, uncertainty, and risk situations. Week 2: Decision Analysis: Bayes Theorem, Decision Making with and without Experimentation, Decision Trees Week 3: Waiting Line Models: Elements of Queuing models, Queuing models based on the birth-and-death process Week 4: Waiting Line Models: Priority-Discipline Queuing Models, Finite population models, Queuing cost models Week 5: Simulation: Discrete-Event Simulation modelling, Random numbers and Random Variates, Input Modelling and Output analysis Week 6: Simulation: Continuous Simulation, System Dynamics Week 7: Network Models: Introduction to Graph theory, Tree and Spanning Tree, Maximal Flow algorithms Week 8: Network Models: Maximal Flow algorithms (continued), Shortest Path algorithms