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Evolutionary Algorithm with Roulette-Tournament Selection for Solving Aquaculture Diet Formulation

Author

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  • Rosshairy Abd Rahman
  • Razamin Ramli
  • Zainoddin Jamari
  • Ku Ruhana Ku-Mahamud

Abstract

The function of operators in an evolutionary algorithm (EA) is very crucial as the operators have a strong effect on the performance of the EA. In this paper, a new selection operator is introduced for a real valued encoding problem, which specifically exists in a shrimp diet formulation problem. This newly developed selection operator is a hybrid between two well-known established selection operators: roulette wheel and binary tournament selection. A comparison of the performance of the proposed operator and the other existing operator was made for evaluation purposes. The result shows that the proposed roulette-tournament selection is better in terms of its ability to provide many good feasible solutions when a population size of 30 is used. Thus, the proposed roulette-tournament is suitable and comparable to established selection for solving a real valued shrimp diet formulation problem. The selection operator can also be generalized to any problems related to EA.

Suggested Citation

  • Rosshairy Abd Rahman & Razamin Ramli & Zainoddin Jamari & Ku Ruhana Ku-Mahamud, 2016. "Evolutionary Algorithm with Roulette-Tournament Selection for Solving Aquaculture Diet Formulation," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-10, June.
    • Handle: RePEc:hin:jnlmpe:3672758
    DOI: 10.1155/2016/3672758
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    Cited by:

    1. Mohammed K. Ibrahim & Umi Kalsom Yusof & Taiseer Abdalla Elfadil Eisa & Maged Nasser, 2023. "Enhanced Genetic Method for Optimizing Multiple Sequence Alignment," Mathematics, MDPI, vol. 11(22), pages 1-23, November.

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