This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office. Credit is recorded as assigned by the study abroad adviser in the Department of Information, Risk, and Operations Management. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence. Transfer credit is awarded for work in an affiliated studies program.

This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office. Credit is recorded as assigned by the study abroad adviser in the Department of Information, Risk, and Operations Management. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence. Transfer credit is awarded for work in an affiliated studies program.

Overview of healthcare operations management. Focus on process diagramming, vocabulary, and analysis of effects of variability on healthcare operations in terms of increasing waiting lines, inventory, and patient safety issues. Focus on modern process improvement methodologies.

The operations or production function and the skills required for analyzing and solving related problems.

An investigation of the operations or production function, and the skills required for analyzing and solving related problems.

Framing, formulating, and applying quantitative optimization and descriptive models to support supply chain and operations management decisions, using spreadsheets and other software. Requires familiarity with spreadsheets.

This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office or the school's BBA Exchange Programs. Credit is recorded as assigned by the study abroad adviser in the Department of Information, Risk, and Operations Management. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence.

Study strategic frameworks for facilitating the digital transformation of supply chains and operations management to align with a firm's business model. Explore the tactical deployment of digital capabilities and the use of data analytics to transform operational processes to improve efficiency, quality, and timing.

Explore strategic issues in procurement and supplier management; a review of competitive analysis and benchmarking; the purchasing role in fulfilling a firm's operational and competitive strategies; supplier evaluation, development, and relationship management; negotiating with suppliers for results; and commodity planning.

Students apply skills in their major area and focus on additional project management skills through group projects conducted in a professional setting. Students may work with a private or a public enterprise.

Analyze the entire flow of information, materials, and services from suppliers through factories and warehouses to the end customer. Examine logistics, supplier selection, and inventory management using case studies, optimization, and simulation.

Learn how information technology is used to coordinate supply chain activities across different industries.

Explore key management challenges and how data may be leveraged to guide decisions and improve operations, with the unifying theme of providing health care services in a manner that leads to lower cost and higher quality.

Study dynamic demand forecasting models based on both data aggregation as well as hierarchical aggregation of point-of-sale predictive analytics. Explore the use of developed predictive dynamic models for operations planning and operations decision maing.

Examine statistical forecasting methods used in business. Discuss Box-Jenkins models; exponential smoothing models; ARCH/GARCH models for varying volatility in financial returns; seasonal adjustment of time series; tests for nonstationary of time series; and modeling multiple time series.

Use data-driven tactics and strategies to predict consumer demand and optimize price and capacity/inventory availability to maximize revenue or profit. Explore demand analytics and revenue management techniques, produce rigorous and practical insights, and develop data analysis and optimization skills, based on business cases, datasets, and exercises. Examine diverse contexts and industries, such as conventional retailing, e-commerce, airline/hotel, and contemporary platform and cloud services (e.g., Uber, Dropbox, Netflix, AWS), by utilizing software (Excel, R, or Python) to build models, conduct optimization, and develop insights for a variety of revenue management examples.

Examine the integration of supply chain management into the product design and development process. Learn skills and knowledge involving product development and incorporating supply chain considerations with an emphasis on designing products that optimize the supply chain while maintaining the products vision from concept to customer.

Discuss the role of supply chain management to increase a firm's competitive performance and understand how that performance affects the economy and society as a whole. Examine supply chain and operations design as well as environmental, social, and governance (ESG) issues. Explore the impact of new business models including e-commerce and automation; contracting; outsourcing and vertical integration, resiliency; and new delivery modalities.

Concepts of computational complexity; the foundation of discrete mathematics and combinatorial theory.

Deterministic queues, priorities, random walks, networks, approximations, and applications.

Tools and concepts for the management of the flow of information, material, product, and cash between the initial suppliers of raw material and the ultimate consumers of finished goods.

Designed to provide guidance to doctoral students interested in research on new approaches to management planning and control of complex systems, and to MBA students interested in evaluating new practices currently being used in management planning and control activities.

Introduction to operations research and optimization, including linear programming, network models, deterministic dynamic programming, decisions under uncertainty, game theory, inventory models, and simulation. Emphasis on mathematical programming models and algorithmic approach of operations research problems.

Designed to provide students, especially those involved in research, with more advanced optimization tools in several broad areas. Includes nonlinear programming, graph theory, integer programming, Markov chains, probabilistic dynamic programming, queueing theory, and metaheuristics. Emphasis on mathematical programming modeling and algorithmic approach of operations research problems.

Supply chain analytics combines analytical tools with technology to identify trends, compare performance and highlight improvement opportunities in supply chain areas including sourcing, inventory management, manufacturing, quality, sales and logistics.

Model formulation: solution algorithms; duality theory; decomposition; sparse matrix issues; sensitivity and parametric analysis; optimization and matrix generation computer software.

Design, analysis, implementation, and use of computer algorithms. Introduction to fundamental data structures, sorting, recursive programs, dynamic data structures, memory management, algorithm design techniques and complexity analysis, and applications in optimization problems. Examples from linear and integer programming, covering, knapsack, graph-theoretic problems, network analysis, and scheduling.

Modeling with simulation languages; random number generation; statistical analysis of input and output; variance reduction techniques; computer software applications.

Mathematical programming models with discrete (integer) decision alternatives. Model formulation and solution algorithms.

Optimization of nonlinear functions of many variables subject to linear or nonlinear constraints. Basic theory, solution algorithms, applications, computer software.

Formulation and solution of large mathematical optimization models. Focus on algorithms that exploit special structure of linear and nonlinear programming models. Applications.

Discrete stochastic systems, queueing processes, inventory models, replacement, renewal theory, Markovian processes.

Selected topics in business analytics.

Strategic problems, policies, models, and concepts for the design and control of new or existing operations systems.

Discuss how the operations of creating value can be better managed to address the challenges of environmental sustainability. Learn about the trade-offs and challenges associated with measuring and reporting emissions, extended producer responsibility, closed-loop supply chains, and business model innovations. Develop critical thinking skills by learning economic theory related to environmental sustainability.

Explore real-world operations challenges through intensive, team-based case work with industry collaborators. Investigate problems such as supply chain disruptions, production planning, and service delivery improvements across multiple sectors. Design and present research-driven solutions to practitioners for review and discussion while strengthening analytical, problem-solving, and presentation skills in an operations context.

Operations research and modeling to assist in decision making through building data models and operations research software systems.

Explore operational challenges arising in outpatient clinics, hospitals, and drug development and production. Examine a combination of business cases and representative data sets. Utilize R as a supporting tool.

Learn how to use analytical tools and conceptual frameworks to make decisions in supply chain contexts. Develop insights about major strategic issues and trade-offs that arise in supply chain management. Collaborate with others in simulated supply chain decision making environments.

Intensive analysis of operations management issues.

Focus on theory, algorithms, and applications of network optimization with emphasis on supply chain operations and applications. Optimize the routing of flows on networks, discover the special structure and properties of network flow problems, and design effective solution methods that exploit these properties.