Applied operations research at the Department of Management Science and Engineering provides quantitative tools to model complex decision making problems in manufacturing and service industries in modern global economy.
Our faculty are experts in optimization, stochastic processes, Markov decision processes, data analytics, and decisions analysis with focus areas in health care, supply chain management and logistics, revenue management and pricing, energy, and manufacturing.
Our research in this area includes applications of descriptive, predictive, and prescriptive analytics tools. Using predictive analytics techniques, our research captures the relationships between inputs and outcomes, and constructs predictions about future outcomes. Using prescriptive analytics, we optimize actions against a complex set of objectives to find best practices and policies under all circumstances. Our faculty have worked with Cancer Care Ontario (CCO) and Dematic Ltd, among others.
Our research aims to improve access to care and to best manage wait lists, optimise health care delivery including patient scheduling, resource allocation, and inventory management, and enhance medical decision making in areas such as cancer screening, infectious disease management, and radiation therapy treatment plans. Our faculty have worked with Ontario Ministry of Health and Long-Term Care, Cancer Care Ontario (CCO), Canada Blood Services, Hamilton Health Sciences, Mayo Clinic, and Grand River and St. Paul Hospitals among others.
Supply chain management and logistics:
Our research in this area comprises the development and application of tools and techniques to aid in the management of integrated manufacturing and logistics systems. We create new knowledge on the design, implementation, operation, and control of these systems, not overlooking the important interfaces with purchasing, transportation, product and process design, inventory management, environment and human resources. Our faculty have worked with Bombardier, Canadian Tire, Nestle, UPS, Navtech Inc., and Dematic Ltd. among others.
Logistics planning and transportation:
Our research in this area includes the decisions related to the design and operation of logistics systems with the aim of delivering the right product, in the right place, at the right time. We are concerned with the design of cost-effective logistics systems integrating a variety of planning decisions ranging from the location of a new distribution centre to efficient pallet loading. Our faculty have expertise in various areas including but not limited to facility location, hub network design, reverse logistics network design, hazardous materials logistics, three-dimensional bin packing, consolidation, and economies of scale.
Revenue management and pricing:
Our research in this area includes applications of statistical tools and methodologies to forecast the demand for products and services, based on which dynamic optimal time-dependent pricing is derived using advanced quantitative techniques. The resulting evidence-based pricing decisions enable industries such as airlines, hospitality, and entertainment to dramatically increase their revenues.
Our research in this area aims to use optimization techniques to model and solve operational and planning problems in smart electricity markets. The proposed techniques use both stochastic and deterministic approaches to solve such models. The results are used to recommend energy policy mechanisms to reduce cost of electricity production, encourage investment in renewable energy sources, increase the reliability of the grid and enhance the overall energy efficiency. Our faculty have worked with California Independent System Operator (CAISO), Federal Energy Regulatory Commission (FERC), and HyrdoOne.