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OPIM 913: Advanced Linear Programming
3.00 Credits
University of Pennsylvania
Prerequisite(s): OPIM 910 or equivalent. In-depth study of the theory and algorithms related to the solution of linear programming problems. Optimality conditions, duality and sensitivity analysis. Primal and dual simplex methods. Interior point methods. Large-scale optimization. Dantzig-Wolfe decomposition.
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OPIM 913 - Advanced Linear Programming
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OPIM 914: Advanced Non-Linear Programming
3.00 Credits
University of Pennsylvania
Staff. Prerequisite(s): OPIM910 or equivalent. Convex sets and functions. Tangent cones. Polar cones. Optimality conditions and duality theory. Methods for unconstrained and constrained optimization. Interior and exterior penalty methods. Lagrangean and augmented Lagrangean methods.
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OPIM 914 - Advanced Non-Linear Programming
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OPIM 915: Advanced Graph Theory
3.00 Credits
University of Pennsylvania
Staff. Deals mainly with algorithmic and computational aspects of graph theory. Topics and problems include reachability and connectivity, setcovering, graph coloring, location of centers, location of medians, trees, shortest path, circuits, traveling salesman problem, network flows, matching, transportation, and assignment problems.
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OPIM 915 - Advanced Graph Theory
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OPIM 916: Advanced Integer Programming
3.00 Credits
University of Pennsylvania
Staff. Prerequisite(s): OPIM 910 or equivalent. In-depth review of solution methods: Lagrangean relaxation and column generation, Benders partitioning, cross- decomposition, surrogate relaxation, cutting planes and valid inequalities, logical processing, probing, branch-andbound, branch-and-price. Study of special problems and applications: matching, location, generalized assignment, traveling salesman, forest planning, production scheduling.
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OPIM 916 - Advanced Integer Programming
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OPIM 920: Empirical Research in Operations Management
3.00 Credits
University of Pennsylvania
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 (you might be surprised to learn that all five bullets listed above has been addressed by Management Science papers) 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.
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OPIM 920 - Empirical Research in Operations Management
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OPIM 930: Stochastic Models
3.00 Credits
University of Pennsylvania
Staff. Prerequisite(s): STAT510 or 550 or equivalent. 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, Markov chains in discrete and continuous time, renewal theory, and martingales. Applications from the areas of inventory, production, finance, queueing and communication systems will be presented throughout the course.
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OPIM 930 - Stochastic Models
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OPIM 931: Stochastic Processes ll
3.00 Credits
University of Pennsylvania
Staff. Prerequisite(s): OPIM930. Crosslisted with STAT 901. Extension of the material presented in OPIM930 to include Markov decision processes, queuing theory, stochastic modeling and optimization.
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OPIM 931 - Stochastic Processes ll
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OPIM 932: Queuing Theory
3.00 Credits
University of Pennsylvania
Staff. Prerequisite(s): OPIM 930 or equivalent. Discrete-state stochastic processes: Markov chains, Markov processes, birth-death processes; M/M/I queue and variants; M/G/I queue and G/M/n queues; priority queues: preemptive and non-preemptive; Networks of queues; jackson networks, BMCP networks, Kelly networks; Little's formula; Dynamic optimization of queues.
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OPIM 932 - Queuing Theory
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OPIM 934: Dynamic Programming and Stochastic Models
3.00 Credits
University of Pennsylvania
Staff. Reviews the theoretical foundations of dynamic programming, stochastic control,and Markov decision processes. Applications in the area of production and inventory, finance, and marketing will be explored. Course requirements include homework, exercises and a research paper.
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OPIM 934 - Dynamic Programming and Stochastic Models
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OPIM 940: Operations Management
3.00 Credits
University of Pennsylvania
Staff. Crosslisted with ESE 620. 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.
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OPIM 940 - Operations Management
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