Paper Info
Title
Experimental Analysis Of The Tournament Size On Genetic Algorithms
Abstract
We perform an experimental study about the effect of the tournament size parameter from the Tournament Selection operator. Tournament Selection is a classic operator for Genetic Algorithms and Genetic Programming. It is simple to implement and has only one control parameter, the tournament size. Even though it is commonly used, most practitioners still rely on rules of thumb when choosing the tournament size. For example, almost all works in the past 15 years use a value of 2 for the tournament size, with little reasoning behind that choice. To understand the role of the tournament size, we run a real-valued GA on 24 BBOB problems with 10, 20 and 40 dimensions. We also vary the crossover operator and the generational policy of the GA. For each combination of the above factors we observe how the quality of the final solution changes with the tournament size. Our findings do not support the indiscriminate use of tournament size 2, and recommend a more careful set up of this parameter.
Year
DOI
Venue
2018
10.1109/SMC.2018.00617
2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
Field
DocType
ISSN
Tournament,Mathematical optimization,Crossover,Computer science,Genetic programming,Artificial intelligence,Rule of thumb,Operator (computer programming),Tournament selection,Genetic algorithm,Machine learning
Conference
1062-922X
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Yuri Cossich Lavinas113.40
Claus Aranha2358.68
Tetsuya Sakurai319845.14
Marcelo Ladeira46213.08