1. Selection (chapter 22~28)
발표자: 임병권

2. Selection
Multiple copies of a solution are placed in a population by deleting some solutions
The essential idea is that a solution having a better fitness must have a higher probability of selection

3. Selective pressure
If a selection operator has a large selective pressure, the population loses diversity in the population quickly => This makes premature problem
A selection operator with a small selection pressure makes a slow convergence and permits enough iterations to properly search the space => Too long time

4. Proportional selection
Map the objective function to fitness
Create a probability distribution proportional to fitness
Draw samples from this distribution

5. Fitness scaling
Supersolution problem  the population loses genetic diversity
Almost solutions have same fitness value  effect of a random selection

6. Roulette wheel Selection
Stochastic universal sampling

7. Tournament selection
A group of q individuals is randomly chosen from the population
This group takes part in a tournament
Fitness scaling 과 무관
빠르고, 병렬처리가 가능

8. Tournament selection #2
With incresing Tournament size q the selection pressure increases
q=6~10 is recommended

9. Rank-based selection
The rank ordering of the fitness of the individuals within the current population determines the probability of selection
Ranking eliminates the need for fitness scaling

10. Rank-based selection #2
Linear ranking
N개의 해중 i번째 순위인 해의 값
Max: 1순위 해의 값, min: 꼴지 해의 값
Max값과 min값으로 선택압을 조정
Nonlinear ranking

11. Boltzmann selection Boltzmann trial
Competition solution i and j, in which i wins with logistic probability
High T: i and j win with nearly equal prob
Low T: the better of the two solutions nearly always win

12. Other selection method
Soft brood selection
Holds a tournament between members of a brood of two parents
Disruptive selection
Has extremely good and bas solutions.
Competitive selection
The fitness of a solution is determined by its interaction with other solutions.

13. Generation gap
Refers to the amount of overlap between parent and offspring
Nonoverlapping(G=1)
parent solutions don’t exist in next generation
Overlapping(0<G<1)
Some parent solutions exist in next generation

14. Generation gap #2
G가 1에 가까울 수록 generational하다고 하고 G가 1/N 에 가까우면 steady-state 하다고 한다.
Steady-state는 빨리 수렴시키는 경향이 있으나 premature convergence의 가능성이 더 크다.