Mathematical programming, Markov processes, queueing theory, inventory models, PERT, CPM, and computer simulation are covered, as well as use of contemporary computer software for problem solving. A case-study approach to problem solving is used. Emphasis on modeling and problem solving. A survey of probabilistic methods for solving decision problems under uncertainty. Probability review, reliability, queuing theory, inventory systems, Markov chain models and Markov decision processes, and discrete-event simulation are covered.
Emphasis is on modeling and problem solving.
Computer simulation as a scientific methodology in operations analysis, with emphasis on model development, implementation, and analysis of results. Discrete-event models, specialized languages, experimental design and output statistics are covered. Extensive computational work is required. Alternative interior point methods are described and the computational complexity of various algorithms is analyzed. An introduction to network problems in operations research, computer science, electrical engineering, and systems engineering.