Babes-Bolyai University of Cluj-Napoca
Faculty of Mathematics and Computer Science
Study Cycle: Master
SUBJECT

Code	Subject	
MI377	Evolutive Programming	

Section	Semester	Hours: C+S+L	Category	Type	
Optimization of computational models- in Hungarian	2	2+2+0		compulsory	

Teaching Staff in Charge	Assoc.Prof. SOOS Anna, Ph.D., asoos@math.ubbcluj.ro	
Aims	Introduction in new optimization methods	
Content	1. Genetic algorithms: representation, evaluation function, genetic operators,  parameters of genetic programs, the algorithm.
2. Function optimization: binary implementation, floiting point  reprezentation, experimental results
3. Prisoner's dilemma, traveling salesman problem: representation, experimental results
4. Simulated annealing: general notions, local optima.
5. Numerical optimization: comparison of the numerical optimization methods.
6. Theoretical approach of genetic algorithms: shemes, characterization, convergence of the algorithm.
7. Evolutionary programming and genetic programming: evolution programs and heuristics. Multiobjective optimization.	
Bibliography	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. D.E. Goldberg: Genetic algoritms in Search, Optimization and machine Learning, Addison Westley, 1989
4. H. Costin, D.Dumitrescu: Retele neuronale, teorie si aplicatii, Teora, 1996 
5. Z. Michalewicz: Genetic Algorithms+ Data Structures Evolutiv Programs, Springer,1996
	
Assessment	Exam