The Wharton School and the University of Pennsylvania must reserve the right to make changes affecting policies, fees, curricula, or any other matters announced here. Course descriptions represent courses that are frequently offered.

While the School endeavors to offer as many of the courses as possible, not all courses are offered every semester. It is important to check with individual departments prior to scheduling classes to determine the availability of courses for any given semester.

OPIM 900: Foundations of Decision Processes

The course is an introduction to research on normative, descriptive and prescriptive models of judgment and choice under uncertainty. We will be studying the underlying theory of decision processes as well as applications in individual, group and organizational choice. Guest speakers will relate the concepts of decision processes to applied problems in their area of expertise. As part of the course there will be a theoretical or empirical term paper on the application of decision processes to each student’s particular area of interest.

OPIM 904: Experimental Economics

Prerequisite: OPIM 900 or permission of instructor.

Many theories in economics and operations and information management can be tested usefully in experiments in which researchers control parameters that are uncontrolled in natural settings. This course presents the theory of the experimental method and validity along with several examples of experimental testing: simple competitive equilibrium, intertemporal competitive equilibrium, asset markets, futures markets, bargaining models, tournaments, reputation-building in repeated games, etc.

OPIM 906: Proseminar in Operations and Information Management

This is a special topics course based on the interdisciplinary ‘Decision Processes’ program at the University of Pennsylvania. The decision processes group is focused on descriptive, normative, and prescriptive aspects of decision-making. This Decision Processes Research Program is made up of a large group of scholars who reside in the Wharton School (Marketing, OPIM, Strategy), Psychology, Engineering and Medicine. Students in the OPIM 906 course will attend the Decision Processes brown bag talk each Monday; brown bag speakers are an interdisciplinary group of scholars, mostly from outside of Penn, whose work is focused on some aspect of decision making. Students will be provided with background readings in advance of each speaker and will have the opportunity to meet with most speakers for more in-depth discussion of presentation topics.

OPIM 910: Concepts of Mathematical Programming

Introduction to mathematical programming for PhD students who would like to be intelligent and sophisticated consumers of mathematical programming theory but do not necessarily plan to specialize in this area. Integer and nonlinear programming are covered, including the fundamentals of each area together with a sense of the state-of-the-art and expected directions of future progress. (Cross listed as SYS 604)

OPIM 913: Advanced Linear Programming and Interior Point Methods

Linear programming (LP) is a branch of Optimization in which one studies the maximization (or minimization) of a linear function subject to linear equality and/or inequality constraints. LP has wide ranging applications from diverse areas such as Economics, Computer Science, Operations Research, Medicine, Finance, Mathematics, as well as every branch of Engineering. It is also the starting point from which one studies more general constrained optimization problems. The course covers the theory of linear programming, the “classical” LP algorithms (like the primal, dual and primal-dual versions of the simplex method), and the new “interior-point” algorithms that have emerged in the past twenty years or so. Toward the end of the course more general optimization problems are briefly discussed including quadratic programming and convex optimization. A broad spectrum of applications will be presented.

OPIM 914: Advanced Nonlinear Programming

This course is concerned with the theory and use of nonlinear programming. The goals of the course are the following: (1) to present students with a knowledge of the state-of-the art in the theory and practice of solving nonlinear programming problems, (2) to provide students with a framework for analyzing algorithms that unifies theoretical and empirical perspectives, and (3) to help each student develop his or her own intuition about algorithm development and algorithm analysis.

OPIM 915: Advanced Graph Theory

Deals mainly with algorithmic and computational aspects of graph theory. Topics and problems include reachability and connectivity, set covering, graph coloring, location of centers, location of medians, trees, shortest path, circuits, traveling salesman problem, network flows, matching, transportation, and assignment problems.

OPIM 916: Advanced Integer Programming

Many optimization models include either integer or 0-1 decision variables. The integrality requirements make the problems much harder to solve than the corresponding continuous optimization problems. The course provides students with a variety of analytical and algorithmic tools for approaching such hard problems. Emphasis is on modeling, as well as on approximate (heuristic), and exact (iterative and enumerative) methods.

OPIM 920: Empirical Research in Operations Management

Empirical research in Operations Management has been repeatedly called for over the last 10-15 years, including calls made from the academic thought leaders in the field as well as by many of the editors of the top academic journals. Remarkably though, most researchers in the field would be pressed to name even three empirical papers published in such journals like Management Science or Operations Research. But, has there really been so little published related to empirical Operations Management? What types of problems in operations are interesting and worthwhile studying from an empirical viewpoint? How can one get started with an empirical research project in Operations Management? These are the questions that are at the heart of this course. Specifically, the objective of this course is to (a) expose doctoral students to the existing empirical literature and (b) to provide them with the training required to engage in an empirical study themselves.

OPIM 930: Stochastic Models I

Prerequisite: STAT 510

This course introduces mathematical models describing and analyzing the behavior of processes that exhibit random components. The theory of stochastic processes will be developed based on elementary probability theory and calculus. Topics include random walks, Poisson processes, and Markov chains in discrete and continuous time. Applications from the areas of inventory, production, finance, queuing and communication systems will be presented throughout the course.

OPIM 931: Stochastic Models II

Prerequisite: STAT 510

This course extends the material presented in OPIM 930 to include renewal theory, martingales, and Brownian motion.

OPIM 932: Queuing Theory

Prerequisite: OPIM 930 and 931 or equivalent.

This course presents the mathematical foundations for the analysis of queueing systems. We will study general results like Little’s law and the PASTA property. We will analyze standard queueing systems (Markovian systems and variations thereof) and simple queueing networks, investigate infinite server models and many server approximations, study GI/G/1 queues through random walk approximations, and read papers on applied queueing models.

OPIM 934: Dynamic Programming

Prerequisite: OPIM 930.

The course goal is to provide a brief but fairly rigorous introduction to the formulation and solution of dynamic programs. Its focus is primarily methodological. We will cover discrete state space problems, over finite or infinite time horizon, with and without discounting. Structured policies and their theoretical foundation will be of particular interest. Computational methods and approximation methods will be addresses. Applications are presented throughout the course, such as inventory policies, production control, financial decisions, and scheduling.

OPIM 940: Operations Management I

Concepts, models, and theories relevant to the management of the processes required to provide goods or services to consumers in both the public and private sectors. Includes production, inventory and distribution functions, scheduling of service or manufacturing activities, facility capacity planning and design, location analysis, product design and choice of technology. The methodological basis for the course includes management science, economic theory, organization theory, and management information system theory.

OPIM 941: Distribution Systems Seminar

Prerequisite: OPIM 940.

Seminar on distribution systems models and theory. Reviews current research in the development and solution of models of distribution systems. Focuses on strategic aspects of supply chain management with the emphasis on game-theoretic models, efficiency and incentives.

OPIM 950: Perspectives on Information Systems

Provides doctoral students in Operations and Information Management and other related fields with a perspective on modern information system methodologies, technologies, and practices. State-of-the-art research on frameworks for analysis, design, and implementation of various types of information systems is presented. Students successfully completing the course should have the skills necessary to specify and implement an information system to support a decision process.

OPIM 951: Seminar on Logic Modeling

Prerequisite: Permission of instructor and some prior knowledge of logic or Prolog.

Seminar on the elements of formal logic necessary to read and contribute to the logic modeling literature, as well as the implementation principles for logic models. The primary topics include elements of sentence and predicate logic, elements of modal logics, elements of semantics, mechanical theorem proving, logic and database, non-monotonic reasoning, planning and the frame problem, logic programming, and meta-interpreters.

OPIM 952: Computational Game Theory

The last few years have seen an explosion of research activity at the boundaries of game theory, computer science, and artificial intelligence. From the CS and AI side, motivations include the use of game theory as a design principle for distributed algorithms and network protocols, and as a foundation for complex autonomous agents engaged in both cooperative activity and strategic competition. From the traditional economic and game theory side, motivations include the development of richer ways of modeling complex and modern problems of strategic interaction and confrontation. This course will survey the progress so far in this exciting and rapidly growing area.

OPIM 955: Research Seminar in Information Systems

This course provides an overview of some of the key Information Systems literature from the perspective of Information Strategy and Economics (ISE) and Information Decision Technologies (IDT). This course is intended to provide an introduction for first year OPIM doctoral students, as well as other Wharton doctoral students, to important core research topics and methods in ISE and IDT in order for students to do research in the field of Information Systems.

OPIM 960: Perspectives on Information Systems Strategy and Economics

Prerequisite: A course in microeconomics theory, such as ECON 680 or 701 or equivalent background, will prove helpful.

Explores economic issues related to information technology, with emphasis on research in organizational or strategic settings. The course will follow a seminar format, with dynamically assigned readings and strong student contribution during class sessions (both as participant and, for one class, as moderator).

OPIM 961: Research Seminar in Information: Strategy, Systems and Economics

This is an advanced doctoral-level research in information strategy and economics that builds on the foundations developed in OPIM 960. Much of the content will be focused on current research areas in information strategy such as the information and organizational economics, information technology and firm performance, search cost and pricing, information and incentives, coordination costs and the boundary of the firm, and the economics of information goods (including pricing and intellectual property protection). In addition, promising empirical approaches such as the use of intelligent agents for data collection or clickstream data analysis will be discussed.

OPIM 986: Individual Study

For students who are studying a specific advanced subject area in Operations and Information Management. Students must submit a proposal outlining and detailing the study area, along with the faculty supervisor’s consent, to the Operations and Information Management doctoral program coordinator. OPIM 989 Topics in Operations and Information Management The specific content of this course varies from semester to semester, depending on student and faculty interests.

OPIM 989: Topics in Operations and Information Management

The specific content of this course varies from semester to semester, depending on student and faculty interests.

OPIM 999: Doctoral Independent Study