Optimal One Day International Cricket Team Selection by Genetic Algorithm

Authors

  • Isuru Kumarasiri Department of Information Technology, Sri Lanka Institute of Information Technology, Malabe 10115, Sri Lanka
  • Sanjeewa Perera Research and Development Center for Mathematical Modeling, Department of Mathematics,University of Colombo, Colombo 00700, Sri Lanka

Keywords:

Genetic Algorithm, Optimal cricket team, Optimization.

Abstract

Cricket is one of the oldest and most popular games in the world. At present it is played professionally and none professionally around the world. Even though the origin of cricket is unknown, there are evidences that it has been played in 16th century. Since then, this remarkable game has developed massively and the first international test cricket match was played in 1877 between Australia and England. Generally there are three types of international cricket matches, which are Test match cricket, one day international cricket and 20-20 cricket. Since the popularity of cricket, it has an immense financial importance. Therefore, winning more matches consistently will generate more financial benefits for the country. Selecting the most suitable cricket team for the given scenario is very vital as far as winning matches are concerned. This system contains various individual characteristics such as players’ batting average, bowling average, Number of wickets and so on. This study describes how to select the optimal one day international squad of Sri Lanka, which consists of 15 players out of 30 players, for the world cup 2015 which is played in Australia. By using Genetic Algorithm method and MATLAB 7 software a system has been constructed to implement the results.

References

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Published

2017-10-24

How to Cite

Kumarasiri, I., & Perera, S. (2017). Optimal One Day International Cricket Team Selection by Genetic Algorithm. International Journal of Sciences: Basic and Applied Research (IJSBAR), 36(4), 213–221. Retrieved from https://www.gssrr.org/index.php/JournalOfBasicAndApplied/article/view/8097

Issue

Vol. 36 No. 4 (2017)

Section

Articles

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