1. komponenta

Lecture type	Total
Lectures	45

* Load is given in academic hour (1 academic hour = 45 minutes)

COURSE AIMS AND OBJECTIVES: Understand the applications of, basic theoretical results, numerical methods for, and challenges in integer programming, network optimization and multiobjective optimization.

COURSE DESCRIPTION AND SYLLABUS:
Integer programming. Examples. The cutting-plane method and the branch-and-bound method.
Network optimization. Algorithmic approaches (with complexity considerations) for: Shortest path tree (Dijkstra; Bellman-Ford), Project planning and management (PERT-CPM), Maximum flow in a transportation network (Ford-Fulkerson and Edmonds-Karp algorithms), Weighted bipartite matching problem (Hungarian method), Transportation problem and minimum-cost network flow problem (network simplex method).
Multi-criteria optimization. Ideal and efficient (Pareto-optimal) points, dual characterizations of optimal points, weighted-sum method in multi-criteria programming, parametric simplex method for multi-objective linear programming, goal programming (reference point method and penalty weight method).

1. Operations research - An introduction, H. Taha, Pearson, 2017.
2. Graphs, networks and algorithms, D. Jungnickel, Springer, 2013.
3. Linear programming and network flows, M. S. Bazaraa, H. D. Sherali, C. M. Shetty, Wiley, 2010.
4. Operacijska istraživanja, Z. Lukač, L. Neralić, Element, 2012.
5. Network optimization: Continuous and discrete models, D. Bertsekas, Athena Scientific, 1998.

Enrollment :
Attended : Introduction to optimization

Examination :
Passed : Introduction to optimization

Izborni predmet 3, 4, 5, 6 - Regular study - Computer Science and Mathematics

Izborni predmet 3, 4, 5, 6 - Regular study - Computer Science and Mathematics