Determination of Selection Method in Genetic Algorithm for Land Suitability
1 Department of Information System, Faculty of Industrial Technology University of Pembangunan Nasional “Veteran” Jawa Timur, Surabaya, Indonesia,
2 Department of Computer Science and Electronic Faculty of Mathematic and Natural Science, Gadjah Mada University, Yogyakarta, Indonesia
3 Faculty of Agriculture Gadjah Mada University, Yogyakarta Indonesia
Genetic Algoirthm is one alternative solution in the field of modeling optimization, automatic programming and machine learning. The purpose of the study was to compare some type of selection methods in Genetic Algorithm for land suitability. Contribution of this research applies the best method to develop region based horticultural commodities. This testing is done by comparing the three methods on the method of selection, the Roulette Wheel, Tournament Selection and Stochastic Universal Sampling. Parameters of the locations used in the test scenarios include Temperature = 27°C, Rainfall = 1200 mm, hummidity = 30%, Cluster fruit = 4, Crossover Probabiitiy (Pc) = 0.6, Mutation Probabilty (Pm) = 0.2 and Epoch = 10. The second test epoch incluides location parameters consist of Temperature = 30°C, Rainfall = 2000 mm, Humidity = 35%, Cluster fruit = 5, Crossover Probability (Pc) = 0.7, Mutation Probability (Pm) = 0.3 and Epoch 10. The conclusion of this study shows that the Roulette Wheel is the best method because it produces more stable and fitness value than the other two methods.
Key words: Method Selection / Genetic Algoritm / Roulette Wheel / Tournament Selection / Stocastic Universal Sampling
© Owned by the authors, published by EDP Sciences, 2016
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