Parent Selection Methods for Genetic Algorithms

(adapted from Graham Kendall, Univ. of Nottingham)

Roulette Wheel Selection

The idea behind the roulette wheel selection technique is that each individual is given a chance to become a parent in proportion to its fitness. It is called roulette wheel selection as the chances of selecting a parent can be seen as spinning a roulette wheel with the size of the slot for each parent being proportional to its fitness. Obviously those with the largest fitness (slot sizes) have more chance of being chosen. Thus, it is possible for one member to dominate all the others and get selected a high proportion of the time.

Roulette wheel selection can be implemented as follows:

1. Sum the fitness of all the population members. Call this TF (total fitness).

2. Generate a random number n, between 0 and TF.

3. Return the first population member whose fitness added to the preceding population members is greater than or equal to n.

Tournament Selection

Two methods are presented:

• Select a pair of individuals at random. Generate a random number, R, between 0 and 1. If R < r use the first individual as a parent. If the R >= r then use the second individual as the parent. This is repeated to select the second parent. (The value of r is a parameter to this method.)

• Select two individuals at random. The individual with the highest evaluation becomes the parent. Repeat to find a second parent.