Combinatorial optimisation
Additional Info
- ECTS credits: 6
- University: Autonomous University of Barcelona
- Semester: 3
- Lecturer 1: Lluis Alseda
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Objectives:
To study the paradigmatic problems (routing, networking, scheduling, etc) that lead to discrete and combinatorial optimisation models, and that are intrinsically difficult in practice due to its high input size. To introduce the modern metaheuristics for approximating the solutions of such problems.
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Topics:
Combinatorial Algorithms. Computational Complexity. Genetic Algorithms. Simulated Annealing. Ant Colony Optimisation. Neural networks in optimisation. Scheduling Problems.
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Books:
G. Ausiello, P. Crescenzi, G. Gambosi, V. Kann, A. Marchetti-Spaccamela, M. Protasi, "Complexity and Approximation".
Springer Verlag, 1999.Sniedovich, M. (2006), "Dijkstra’s algorithm revisited: the dynamic
programming connexion Journal of Control and Cybernetics/ *35* (3): 599–620.
Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L,
"Introduction to Algorithms" (first edition ed.). MIT Press and McGraw-Hill.
Judea Pearl, "Heuristics: Intelligent Search Strategies for Computer
Problem Solving", Addison-Wesley Pub (Sd) 1984.
