The course will give a firm understanding of tractable problems and how to empirically estimate the computational resources (storage and time) required by an algorithm. Classic algorithms such as simplex method and big M method will be introduced to solve tractable problems. In addition, intractable problems such as integer programming problems are also introduced. The students will explore how classical solution methods such as linear programming and dynamic programming break down in intractable cases. The course will introduce advanced algorithms to solve intractable problems. Students study alternative solution methods such as stochastic and heuristic approximation methods such as tabu search, branch and bound, relaxation, genetic algorithms and simulated annealing.
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