The following are courses I teach at Northern Illinois University.
Introduction to warehousing and distribution center operations and their roles in supply chains, modern material handling equipment, and algorithms involved in the design and operation of warehouses and distribution centers.
A broad introduction to the key analytical tools and techniques to effectively extract and interpret complex patterns found in large amounts of data. Reinforce statistic modeling skills, and develop core skills to make informed decisions. Major topics include: data manipulation and transformation, data visualization, sampling methods, classification methods, linear regression analysis.
Design and analysis of industrial systems using computer simulation models. Choice of input distributions, generation of random variates, design and construction of simulation models and experiments, and interpretation of generated output.
Advanced theory and methods of inventory control systems. Underlying behavior of production systems. Modern approaches to production planning and operations management.
Introduction to facilities location problems and factors affecting the selection criteria. Discussion of quantitative models and algorithms to choose the location considering various costs such as transportation, inventory, and fixed cost to open and operate a facility.
Applying analytical tools and techniques to effectively extract and interpret complex patterns found in large amounts of engineering data. Develop predictive modeling skills to make informed decisions on problems that occur in engineering practice. Major topics include: data visualization, modeling, classification methods, clustering, and learning algorithms.
Formulation and solution techniques for linear programming and network flow problems. Simplex method, theory, and computation. Duality theory, sensitivity analysis. Maximum flow minimum cut theorem. Shortest routes, minimum cost flows.
Advanced simulation concepts; event scheduling, process interaction, and continuous modeling techniques. Design and analysis of simulation experiments; probability and statistics related to simulation such as length of run, probability distribution interference, variance reduction, and stopping rules.