Transport Optimization
Abbreviation: OPTPROPR Load: 30(L) + 15(E) + 0(LE) + 0(S) + 0(FLE) + 0(PEE)
Lecturers in charge: dr. sc. Tonči Carić
Lecturers: Martina Erdelić mag. ing. traff. ( Exercises )
Tomislav Erdelić mag. ing. el. techn. inf. ( Exercises )
Course description: Basic concepts of the graph theory. Euler graphs, Hamiltonian path, and Travelling salesman problem. Mathematical model of the Vehicle routing problem, complexity of the problem estimation, and various models in practice. Heuristically solving NP-hard problems with examples of vehicle routing problems. Location-allocation problems (Multisource Weber problem), clustering problems. Bin packing problem. Integer linear program and optimization process. Methods for solving CLP (exact algorithms, approximation algorithms, heuristic algorithms). NP-hard and NP-complete problems. Exact methods (backtracking, branch and bound). Heuristics methods (greedy heuristic, local search, simulated annealing). Scheduling problems.
Lecture languages: hr
Compulsory literature:
1. Carić, T.: Autorizirana predavanja iz Optimizacije prometnih procesa, Fakultet prometnih znanosti, 2013.
2. Corne, D., Dorigo, M., Glover, F.: New Ideas in Optimization, Mc Graw Hill, 1999.
Recommended literature:
3. Hoos, H., Stutzle, T.: Stohastic Local Search Foundations and Applications, Morgan Kaufmann, 2005.
4. Crainic, T.G., Laporte, G.: Fleet Managment and Logistics, Kluwer, 1998.
L - Lectures
E - Exercises
LE - Laboratory exercises
S - Seminar
FLE - Practical foreign language exercises
PEE - Physical education excercises
* - Not graded