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Learning Outcomes

TopDiscrete optimization is the study of problems where the goal is to find an optimal arrangement from among a finite set of possible arrangements. Discrete problems are also called combinatorial optimization problems. Many applications in business, industry, and computer science lead to such problems, and we will touch on the theory behind these applications. The course takes a modern view of discrete optimization and covers the main areas of application and the main optimization algorithms. It covers the following topics (tentative): • integer and combinatorial optimization: introduction and basic definitions • alternative formulations • optimality, relaxation and bounds • Graph Theory and Network Flow • integral polyhedral, including matching problems, matroid and the Matroid Greedy algorithm • polyhedral approaches: theory of valid inequalities, cutting-plane algorithms The course also discusses how these approaches can be used to tackle problems arising in modern service system, including static and dynamic matching markets, ad words allocation, pricing and assortment optimization etc.

Prerequisites

TopBDC6111/IE6001 Foundations of Optimization

Workload

Top3-0-0-3-4

Workload Components : A-B-C-D-E
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E: no. of hours for preparatory work by a student per week