Courses tagged with "Infor" (219)

This half-semester course provides an introduction to microeconomic theory designed to meet the needs of students in an economics Ph.D. program. Some parts of the course are designed to teach material that all graduate students should know. Others are used to introduce methodologies. Students should be comfortable with multivariable calculus, linear algebra, and basic real analysis.

This course offers an introduction to noncooperative game theory. The course is intended both for graduate students who wish to develop a solid background in game theory in order to pursue research in the applied fields of economics and related disciplines, and for students wishing to specialize in economic theory. While the course is designed for graduate students in economics, it is open to all students who have taken and passed 14.121.

This course covers models of individual decision-making under certainty and uncertainty. Applications include risk sharing and financial markets; contracts and information economics; village economies and national development; models with money and credit; trade, spatial economics and differentiated commodities.

The topic of the class is information economics. The purpose is to give an introduction to some of the main subjects in this field: risk sharing, moral hazard, adverse selection (signaling, screening), mechanism design, decision making under uncertainty. These subjects (and others) will be treated in more depth in the advanced theory courses on Contract Theory.

Negotiation and Conflict Management presents negotiation theory – strategies and styles – within an employment context. 15.667 meets only eleven times, with a different topic each week, which is why students should commit to attending all classes. In addition to the theory and exercises presented in class, students practice negotiating with role-playing simulations that cover a range of topics. Students also learn how to negotiate in difficult situations, which include abrasiveness, racism, sexism, whistle-blowing, and emergencies. The course covers conflict management as a first party and as a third party: third-party skills include helping others deal directly with their conflicts, mediation, investigation, arbitration, and helping the system change as a result of a dispute.

Learning and grading in 15.667 is based on: readings, simulations and class discussions, four self-assessments, your analysis of the negotiations of others, writing each week in your journal, and writing three Little Papers.

15.082J/6.855J/ESD.78J is a graduate subject in the theory and practice of network flows and its extensions. Network flow problems form a subclass of linear programming problems with applications to transportation, logistics, manufacturing, computer science, project management, and finance, as well as a number of other domains. This subject will survey some of the applications of network flows and focus on key special cases of network flow problems including the following: the shortest path problem, the maximum flow problem, the minimum cost flow problem, and the multi-commodity flow problem. We will also consider other extensions of network flow problems.

Networks are ubiquitous in our modern society. The World Wide Web that links us to and enables information flows with the rest of the world is the most visible example. It is, however, only one of many networks within which we are situated. Our social life is organized around networks of friends and colleagues. These networks determine our information, influence our opinions, and shape our political attitudes. They also link us, often through important but weak ties, to everybody else in the United States and in the world. Economic and financial markets also look much more like networks than anonymous marketplaces. Firms interact with the same suppliers and customers and use Web-like supply chains. Financial linkages, both among banks and between consumers, companies and banks, also form a network over which funds flow and risks are shared. Systemic risk in financial markets often results from the counterparty risks created within this financial network. Food chains, interacting biological systems and the spread and containment of epidemics are some of the other natural and social phenomena that exhibit a marked networked structure.

This course will introduce the tools for the study of networks. It will show how certain common principles permeate the functioning of these diverse networks and how the same issues related to robustness, fragility, and interlinkages arise in several different types of networks.

This course focuses on recent developments in econometrics, especially structural estimation. The topics include nonseparable models, models of imperfect competition, auction models, duration models, and nonlinear panel data. Results are illustrated with economic applications.

This course presents micro-econometric models, including large sample theory for estimation and hypothesis testing, generalized method of moments (GMM), estimation of censored and truncated specifications, quantile regression, structural estimation, nonparametric and semiparametric estimation, treatment effects, panel data, bootstrapping, simulation methods, and Bayesian methods. The methods are illustrated with economic applications.

This course introduces students to the fundamentals of nonlinear optimization theory and methods. Topics include unconstrained and constrained optimization, linear and quadratic programming, Lagrange and conic duality theory, interior-point algorithms and theory, Lagrangian relaxation, generalized programming, and semi-definite programming. Algorithmic methods used in the class include steepest descent, Newton's method, conditional gradient and subgradient optimization, interior-point methods and penalty and barrier methods.

This course introduces students to the fundamentals of nonlinear optimization theory and methods. Topics include unconstrained and constrained optimization, linear and quadratic programming, Lagrange and conic duality theory, interior-point algorithms and theory, Lagrangian relaxation, generalized programming, and semi-definite programming. Algorithmic methods used in the class include steepest descent, Newton's method, conditional gradient and subgradient optimization, interior-point methods and penalty and barrier methods.

Our objective in this course is to introduce you to concepts and techniques related to the design, planning, control, and improvement of manufacturing and service operations. The course begins with a holistic view of operations, where we stress the coordination of product development, process management, and supply chain management. As the course progresses, we will investigate various aspects of each of these three tiers of operations in detail. We will cover topics in the areas of process analysis, materials management, production scheduling, quality improvement, and product design.

To pursue the course objective most effectively, you will have to:

1. Study the assigned reading materials.
2. Prepare and discuss cases, readings, and exercises in class.
3. Prepare written analyses of cases.