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Optimization Models for Business Operations
This course teaches the students how to formulate and solve deterministic
optimization models, including linear, integer, nonlinear, network and dynamic
programming problems. The students will learn to use appropriate computer
modeling languages to solve exercises and applications from the business world.
The objective of the course is to endow the students with complete command over
a set of tools that can be used in business operations. This includes knowing
how to formulate an optimization problem, how to solve that problem using
computer modeling languages, which analytical theories and computational
methods underlie the solution procedure, and how to interpret the result and
its sensitivity analysis.
Stochastic Models for Business Operations
This is a foundation course in applied stochastic processes with emphasis on
modeling real life phenomena with probabilistic reasoning, especially relating
to operations management. Over the past several decades, stochastic models
have proven to be highly effective in optimizing the use of resources within
many areas in business. These models use some basic building blocks from
probability theory and stochastic processes to model decision problems under
uncertainty related to business operations. Researchers in operations
management have actively contributed to these models for a wide variety of
applications. There are also other areas and disciplines where stochastic
processes have great use. Topics to be covered include a review of elementary
probability theory with particular attention to conditional expectation; the
Poisson process, and Markov processes. Applications to operations management
especially involving queuing, reliability, and inventory will be discussed.
Advanced Business Processes
This course offers concepts and techniques to structure, manage, and improve a
firm's recurring business processes. We will cover both theoretical models as
well as practical examples. The content of the course is applicable to banks,
grocery stores, and hospitals, for example, as to traditional manufacturing.
This course is essential to students aspiring to become consultants,
entrepreneurs, general managers, or academic researchers. They will learn how
to manage the business processes of a firm, and how these processes affect and
are affected by their business decisions. This is also a foundation course that
prepares students to do rigorous academic research in Operations Management.
Advanced Management Science
This course covers some advanced mathematical and computing techniques to
solve problems in business operations. It equips students with the
necessary skills to do rigorous research in operations management. Possible
topics covered by this course include dynamic programming, Markov decision
process, game theory, heuristics, dynamical systems, and simulation.
Research Topics in Operations Management
The objective of this course is to introduce master’s students to the state-of-the-art research in operations management (OM), to provide a forum to communicate research ideas between OM faculty and students, and to initiate master’s students to formulate and analyze a research problem that eventually may extend to master’s dissertation. Besides the faculty oriented research topics, selected analytical modeling tools will be introduced in the course, which include economic order quantity model and different variants of newsvendor problem.
Decision Analysis
The objective of this seminar is to equip students with decision-making skills under uncertainty. The seminar covers some mathematical tools for describing and reasoning about decisions, including Bayesian approaches, utility and loss, decision tree and influence diagrams, etc. Also, it will cover the application of the theoretic tools to real world problems.
Inventory Models
The role of inventory management cannot be overstated in managing an efficient supply chain. In this seminar, we focus on various inventory management models. Topics to be discussed include, but not limited to classification of inventory systems, deterministic demand models, stochastic demand models (single- and multi-period), and the impact of leadtime. Variants of the abovementioned basic models will be discussed. These include adding consideration of competition, information, etc. The seminar will be conducted mainly through reading and presenting papers.
Manufacturing and Logistics Operations
This seminar engages students with the underlying concepts of the operations of manufacturing and logistics systems. Students will learn mathematical tools to analyze the systems and to improve their performance. This seminar is especially useful for students who wish to work on research problems in manufacturing and logistics operations management.
Optimization
This seminar provides a comprehensive introduction to deterministic optimization in operations research including mathematical programmes (linear, nonlinear, integer, and network), algorithms, and applications. Our aim is to provide both tactical knowledge and high-level insights for general managers and management consultants, and to increase their competitiveness in various industries such as transportation engineering, trading, merchandising, manufacturing, retailing, and logistics.
Planning and Scheduling in Manufacturing and Services
This seminar focuses on planning and scheduling applications in manufacturing and services industries. Analytic and heuristic techniques used to allocate resources to activities in project scheduling, planning and scheduling in supply chains, reservations and timetabling, tournament scheduling, transportation and workforce scheduling are studied.
Production and Distribution Systems
This seminar will cover a range of current research topics in production and distribution systems. While basic concepts on inventory management will be covered, we will focus on research issues in multi-level production and distribution systems. In particular, we will be discussing representative papers in the area of multi-level production and distribution systems, and students should focus on the modeling framework and the main results, as well as the managerial implications.
Revenue Management
This seminar covers both theory and practice of revenue management (RM). RM has gained attention recently as one of the most successful application areas of operations research. Both academic and industrial research on methodology of RM has grown rapidly. This seminar provides students analytical training in both operations research and economics. It also gives students a qualitative understanding of the business context, such as airlines, hotel chains, and car rental companies.
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