Quantitative Analysis for Business Decisions

This is an intensive course for advanced graduate and Ph.D. students. Emphasis is placed on modeling as an aid to managerial decision-making and also on algorithmic concepts associated with various operations research methods. The tools to be studied are divided into deterministic optimization, dynamic optimization, and stochastic models. Typical optimization topics include linear programming, network models, integer programming, and dynamic programming. Stochastic modeling approaches include Markov chains, queuing, and simulation models. Available software will facilitate the development of modeling and analysis skills. The role of operations research within the organization and the importance of employing a systems orientation are discussed. Throughout, the student is exposed to a wide variety of decision problems and management planning issues in the areas of marketing, economics, finance, accounting, production, personnel, and health administration.