Tournament selection is a method of selecting an individual from a population of individuals in a genetic algorithm. Tournament selection involves running several "tournaments" among a few individuals chosen at random from the population. The winner of each tournament is selected for crossover. Selection pressure, a probabilistic measure of a chromosome's likelihood of participation in the tournament based on the participant selection pool size, is easily adjusted by changing the tournament size, the reason is that if the tournament size is larger, weak individuals have a smaller chance to be selected, because, if a weak individual is selected to be in a tournament, there is a higher probability that a stronger individual is also in that tournament. The tournament selection method may be described in pseudo code: choose k individuals from the population at random choose the best individual from the tournament with probability p choose the second best individual with probability p* choose the third best individual with probability p* and so on Deterministic tournament selection selects the best individual in any tournament. A 1-way tournament selection is equivalent to random selection. There are two variants of the selection: with and without replacement. The variant without replacement guarantees that when selecting N individuals from a population of N elements, each individual participates in exactly k tournaments. An algorithm is proposed in. Note that depending on the number of elements selected, selection without replacement does not guarantee that no individual is selected more than once. It just guarantees that each individual has an equal chance of participating in the same number of tournaments. In comparison with the fitness proportionate selection method, tournament selection is often implemented in practice due to its lack of stochastic noise. Tournament selection has several benefits over alternative selection methods for genetic algorithms : it is efficient to code, works on parallel architectures and allows the selection pressure to be easily adjusted. Tournament selection has also been shown to be independent of the scaling of the genetic algorithm fitness function in some classifier systems.
Tournament scheduling
Tournament scheduling, a variant of tournament selection, can be used as a resource-efficient method for scheduling computing tasks, such as in the context of a cloud computing service. Here the problem is to share tasks equally between resources, such as individual servers, when the load that each task will require cannot be determined in advance, and where it would be inefficient or slow to poll every available server to determine its current load. Failure to schedule tasks appropriately may lead to individual tasks becoming resource-constrained, or even fail. Tournament scheduling proceeds by polling servers in a small, randomly-selected, pool, and assigning the task to the server with the current most capacity. In many contexts this gives an efficient and robust tradeoff between the resource and time required to determine the load on each server, and ensuring an equitable distribution of load.
