CoursesUniversity of FloridaEIN 4343. Inventory and Supply Chain Systems. (Undergraduate senior core course) Topics: Demand forecasting, inventory control, EOQ model, news-vendors problem, fundamentals of linear programming and network optimization, classical network flow models, the bullwhip effect, facility location problem, capaciated/uncapacitated lot-sizing problem, supply chain risk management. University of MichiganIOE 310: Introduction to Optimization. (Undergraduate core course) Topics: Matrix operations, basic convex analysis, mathematical modeling with emphasis on linear programming; introduction to integer programming and network optimization; simplex algorithms, engineering applications, relevant software (e.g., Excel solver, AMPL). IOE 510 (Math 561) (OMS 518): Linear Programming I. (Master-level graduate course) Topics: Mathematical modeling, linear algebra and matrices, the simplex algorithm, duality theory and optimality conditions, sensitivity analysis, network flows, combinatorial optimization, computations in AMPL, basics in decomposition, integer programming, and stochastic optimization. IOE 512: Dynamic Programming (Master-level graduate course) Topics: The techniques of recursive optimization and their use in solving multistage decision problems, applications to various types of problems, including an introduction to Markov decision processes and reinforcement learning. IOE 591: Special Topic on Transportation System Optimization (Master-level graduate course) Topics: Examples of smart transportation, mobility and logistic systems and their use in modern society. Introduction of networks and network flow models for these systems and how to optimize resource planning and operational decisions related to smart mobility and transportation. Descriptions of different decision-making models and solution approaches for specific problems related to the use of smart transportation in industry. IOE 612: Network Flows. (Advanced graduate course) Topics: Basic graph theories, minimum cost flow, shortest path, minimum spanning tree, maximum flow (minimum cut), network simplex method, network interdiction and its applications in homeland security, social networks, epidemic control. IOE 691: Stochastic and Robust Optimization (Advanced graduate course) Co-instruct with Prof. Marina Epelman. Topics: Sampling methods, stochastic mixed-integer programming models, decomposition methods, large-scale optimization, stochastic dynamic programming, approximation algorithms, (joint) chance-constrained programming, theories and applications of robust optimization, discussions of data driven models and relationship between different stochastic programs. ENGR 455: Multidisciplinary Project Design. (Undergraduate multidisciplinary course)
Outreach ActivitiesOR/IE Tools for Fighting COVID-19 A collection of our group's work on Optimization and Data Analytics Tools for Addressing COVID-19 Related Problems . My article on "A Summary of Operations Research and Industrial Engineering Tool for Fighting COVID-19." My article on the Conversation about how to design and perform COVID-19 testing when supplies are scarce. Power Optimization Game The Power Optimization Game is an Excel macro-based multiplayer-game designed for high school age students (Grades 9-12). The purpose of the game is for students to compete and provide adequate power for a random system, while trying to use the lowest dollar cost and lowest carbon emissions cost. The game demonstrates concepts of varying loads, reserves, and uncertainty. Students have the option to choose between wind power, coal, and gas as sources for electricity. This game was created and designed by Joy Chang and Spencer Maroukis. Further modifications were made by Fanny Pinto Delgado and Abdi Zeynu. The faculty sponsors for this project were Siqian Shen, Johanna Mathieu, and Heath Hofmann. This game was used for the 2016 Power Up Tech Camp and the 2016 Tech Day Design Competition. The creation of this game is part of our NSF CyberSEES project (CCF-1442495) and the involved undergraduate students were supported by its REU supplement. If you are interested in using it for teaching/research purpose, please download all the materials and game instructions at: Power Game |