PENGARUH OPERATOR CROSSOVER TERHADAP RUNNING TIME UNTUK PENCARIAN SOLUSI 10 NUMERIC OPTIMIZATION PROBLEMS (NOP) DALAM ALGORITMA GENETIKA BINER - , Syariful Alim S.Kom; , Drs Retantyo Wardoyo M.Sc, Ph.D ([Yogyakarta] : Universitas Gadjah Mada, 2012)
Binary genetics algorithm constitutes technical optimization based on species evolution which actually confines natural selection that is crossover and mutation for survival. It draws an immense attention due to its capability of technical optimization or problem solving for numeric problems, especially in its development of crossover method. This research is aimed to design and create software to solve 10 Numeric Optimization Problem (NOP) through 10 crossover operator application of binary genetics algorithm. Crossover probability and mutation were employed randomly and population was limited to 20 population each generation. Application, then, run 1000 generations each 100 times which provided 100 databases. This research comes into result that one running time of all operators for 1000 generations was around 15-16 minutes, Shuffle Crossover Operators are minimum value of 5 NOP, Two Point and Multi Point Crossover is minimum value of 2 NOP, One Bit Adaptation, Three Parent and One Point Crossover is minimum value of 1NOP. The fastest time of Three Parent Crossover is 153.55 minute and the slowest time of Partially Matched and Shuffle Crossover 155.62 minutes.