Analisa Penerapan Model Algoritma Fuzzy Evolusi (Studi Kasus : Penentuan Menu Makanan Diabetes Melitus) - Farlin Yosry; Erick Alfons Lisangan (TEMATIKA: Jurnal Penelitian Teknik Informatika dan Sistem Informasi, 2017)
Adaptive fuzzy evolutionary algorithm control genetic parameters based on population diversity to avoid premature convergence. However, population diversity isn’t guarantee achieving optimum global solution. This research aims to model adaptive fuzzy with fitness goals and analyze influence of genetic parameters, fuzzy, crossover and mutation technique towards case study DM food menu determination that has fitness goal as calorie needs. This research results show that adaptive fuzzy with fitness goals is able to produce solution that has fitness with good degree of accuracy. Crossover relies on fuzzy and mutation while fuzzy adaptive, chromosome mutation and larger population can produce better fitness.