COMBINATORIAL OPTIMIZATION: Data Structures. Complexity Theory. Assignment Problem. Matching Problem. Minimum Spanning Tree and matroids. Shortest Path Problem. Dynamic Programming. NP-Hard Problems. Branch-and-Bound. Approximation Algorithms.

NETWORK OPTIMIZATION: Classical problems in network optimization: minimum spanning tree, shortest path, transportation problems, assignment problems, minimum cost flow and maximum flow problem. Primal, dual and primal-dual algorithms. Dynamic programming and heuristics. Large-scale optimization: telecommunication, computers and transportation networks. Parallel computing and complexity theory.

TOPICS ON OPTIMIZATION: Variable course syllabus depending on the emphasis offered on Optimization.

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