Babes-Bolyai University of Cluj-Napoca
Faculty of Mathematics and Computer Science
Study Cycle: Master
SUBJECT
| MMC1010 | Stochastic Search Methods |
| Teaching Staff in Charge |
Assoc.Prof. SOOS Anna, Ph.D., asoos math.ubbcluj.ro |
| Aims |
|
Introduction in stochastic search and optimization methods and algorithms.
At the completion of this course, the student should be able to use these algorithms for solving real problems |
| Content |
|
Stochastic processes. Markov chains. Gaussian processes.
Introduction to stochastic search and optimization. Local and global optima. Computer simulation. Stochastic optimization algoritms. Convergence of them. Stochastic gradient method. Simulated annealing. Metropolis algorithm. Genetic algorithms. Schema theorem. Convergence of this algorithm. Evolutionary strategies. Evolutionary programming. Tabu search. Binary search. Aplications. Markov chains and Monte Carlo methods. |
| References |
|
1. A. Almos, S. Gyori, G. Horvath, A. Koczy: Genetikus algoritmusok, Typotex, 2002
2. Thomas Bäck. Evolutionary algorithms in theory and practice. OxfordUniversity Press, New York, 1996. 3. M. Mitzenmacher, E. Upfal: Probability and Computing, Cambridge University Press, 2005 4. A. Noga: The probabilistic method, Wiley, 2001 5. H.P. Schwefel. Evolution and Optimum Seeking. Wiley, 1995. 6. A. Soós: A valószínűségszámítás elemei, Egyetemi Kiadó, Kolozsvár, 2001 7. J.C. Spall: Introduction to Stochastic Search and Optimization, Amazon, 2002 |
| Assessment |
|
3 problems solved by computer, 30%.
Solving a real problem by stochastic algorithm 70%. |
| Links: | Syllabus for all subjects Romanian version for this subject Rtf format for this subject |