Contents
Introduction to software tools for modeling and data analysis Exposure to computational software for optimization. Use of some software tools such as AMPL/ CPLEX/ Spreadsheet Solver/ LINDO/ LINGO/ Neos Solver/ MATLAB for solving and analyzing optimization problems. Building models, representing input data, results, interpretation & sensitivity analysis.
Exposure to statistical packages for data analysis. Use of R/ SAS/ SPSS/ Excel-spreadsheet. Summarizing data with descriptive statistics, computing statistics, statistical estimation & tests
Notion of simulation and effect of randomness. Introduction to Monte Carlo simulation. Simulation of reliability, inventory, queueing systems and basic Markov models, computing performance measures.
References
- Wayne L. Winston (2004) Data Analysis and Business Modeling with Microsoft Excel, Microsoft Press..
- Robert Fourer, David M. Gay and Brian W. Kernighan (2003) AMPL: A Modeling Language for Mathematical Programming, 2nd edition, Duxbury Resource Center..
- Sheldon M. Ross (2004) Introduction to Probability and Statistics for Engineers and Scientists, 3rd edition, Academic Press..
- Jerry Banks, Barry L. Nelson and David Nicol (2004) Discrete Event System Simulation, 4th edition, Prentice Hall of India.