A first-year graduate course in algorithms. Emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Data structures. Network flows. Linear programming. Computational geometry. Approximation algorithms.

This course is a survey of analytic tools, approaches, and techniques which are useful in the design and operation of logistics systems and integrated supply chains. The material is taught from a managerial perspective, with an emphasis on where and how specific tools can be used to improve the overall performance and reduce the total cost of a supply chain. There is a strong emphasis on the development and use of fundamental models to illustrate the underlying concepts involved in both intra- and inter-company logistics operations. The following topics are covered: Demand Forecasting Tools, Inventory Control Algorithms, Transportation Operations and Management, Vehicle Routing, Scheduling, Fleet Dispatching Algorithms and Approaches, Optimization of Transportation Carrier Operations, Supply Chain Network Design, Procurement, Sourcing, and Auctions (including Combinatorial Auctions), Management and Minimization of Supply Chain Uncertainty and Supply Contracts and Collaboration. In addition to model development, the course uses examples from industry to provide illustrations of the concepts in practice. This is not, however, a case study course.

Math in Society is a free, open textbook. This book is a survey of mathematical topics, most non-algebraic, appropriate for a college-level topics course for liberal arts majors. The text is designed so that most chapters are independent, allowing the instructor to choose a selection of topics to be covered. Emphasis is placed on the applicability of the mathematics. Core material for each topic is covered in the main text, with additional depth available through exploration exercises appropriate for in-class, group, or individual investigation. This book is appropriate for Math 107 (Washington State Community Colleges common course number).

Introduces students to problems and analysis related to the design, planning, control, and improvement of manufacturing and service operations. Includes process analysis, project analysis, materials management, production planning and scheduling, quality management, supply chain management, reengineering, design for manufacturing, capacity and facilities planning, and operations strategy. This course will introduce concepts and techniques for design, planning and control of manufacturing and service operations. The course provides basic definitions of operations management terms, tools and techniques for analyzing operations, and strategic context for making operational decisions. We present the material in five modules: Operations Analysis Coordination and Planning Quality Management Project Management Logistics and Supply Chain Managemen.

1.040 covers three important aspects of construction project management: (1) the theory, methods and quantitative tools used to effectively plan, organize, and control construction projects; (2) efficient management methods revealed through practice and research; and (3) hands-on, practical project management knowledge from on-site situations and field trips. The course relies on a basic project management framework in which the project life-cycle is broken into organizing, planning, monitoring, controlling and learning from old and current construction projects. Within the framework, students learn the methodologies and tools necessary for each aspect of the process as well as the theories upon which these are built. By the end of the term they are able to adapt and apply the framework to effectively manage a construction project in an Architecture/Engineering/Construction (A/E/C) organization.

6.780 covers statistical modeling and the control of semiconductor fabrication processes and plants. Topics include design of experiments, response surface modeling, and process optimization; defect and parametric yield modeling; process/device/circuit yield optimization; monitoring, diagnosis, and feedback control of equipment and processes; analysis and scheduling of semiconductor manufacturing operations.

Application-oriented introduction to systems optimization focusing on understanding system tradeoffs. Introduces modeling methodology (linear, network, integer, nonlinear programming, and heuristics), modeling tools (sensitivity and postoptimality analysis), software, and applications in production planning and scheduling, inventory planning, supply network optimization, project scheduling, telecommunications, facility sizing and capacity expansion, product development, yield management, electronic trading, and finance.

Task scheduling allows multiple processes to run on a system without competing for resources.