Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Calculating the expected loss of diversity of selection schemes
Evolutionary Computation
Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
A Mathematical Analysis of Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
Fighting Bloat with Nonparametric Parsimony Pressure
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Lexicographic Parsimony Pressure
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Global Selection Methods for Massively Parallel Computers
Selected Papers from AISB Workshop on Evolutionary Computing
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Backward-chaining evolutionary algorithms
Artificial Intelligence
Another investigation on tournament selection: modelling and visualisation
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Genetic algorithms, selection schemes, and the varying effects of noise
Evolutionary Computation
A comparison of selection schemes used in evolutionary algorithms
Evolutionary Computation
Understanding EA dynamics via population fitness distributions
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
A review of tournament selection in genetic programming
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
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Standard tournament selection samples individuals with replacement. The sampling-with-replacement strategy has its advantages but also has issues. One of the commonly recognised issues is that it is possible to have the same individual sampled multiple times in a tournament. Although the impact of this multi-sampled issue on genetic programming is not clear, some researchers believe that it may lower the probability of some good individuals being sampled or selected. One solution is to use an alternative tournament selection (no-replacement tournament selection), which samples individuals in a tournament without replacement. This paper analyses no-replacement tournament selection to investigate the impact of the scheme and the importance of the issue. Theoretical simulations show that when common tournament sizes and population sizes are used, no-replacement tournament selection does not make the selection behaviour significantly different from that in the standard one and that the multi-sampled issue seldom occurs. In general, the issue is not crucial to the selection behaviour of standard tournament selection.