Afshar, M., Toloie, A., Nazeri, F. (2014). Optimization of e-Learning Model Using Fuzzy Genetic Algorithm. International Journal of Information, Security and Systems Management, 3(1), 281-285.
Mohammad Ali Afshar; Abbas Toloie; Fateme Nazeri. "Optimization of e-Learning Model Using Fuzzy Genetic Algorithm". International Journal of Information, Security and Systems Management, 3, 1, 2014, 281-285.
Afshar, M., Toloie, A., Nazeri, F. (2014). 'Optimization of e-Learning Model Using Fuzzy Genetic Algorithm', International Journal of Information, Security and Systems Management, 3(1), pp. 281-285.
Afshar, M., Toloie, A., Nazeri, F. Optimization of e-Learning Model Using Fuzzy Genetic Algorithm. International Journal of Information, Security and Systems Management, 2014; 3(1): 281-285.
Optimization of e-Learning Model Using Fuzzy Genetic Algorithm
2Industrial Management Department, Science and Research Branch, Islamic Azad University, Tehran, Iran
3Master of Science, Department of Information Technology Management, Electrinic Branch, Islamic Azad University, Tehran, Iran
Abstract
E-learning model is examined of three major dimensions. And each dimension has a range of indicators that is effective in optimization and modeling, in many optimization problems in the modeling, target function or constraints may change over time that as a result optimization of these problems can also be changed. If any of these undetermined events be considered in the optimization process, this is called optimization problem. Many problems in the real-world are dynamic and uncertain and solve them as static are not appropriate. In this paper, for the first time a fuzzy genetic algorithm for optimization and modeling e-learning is presented. Method is that we create a fuzzy model at first, and then we perform optimization by genetic. The results of proposed algorithm on mobile peaks benchmark that are already best-known benchmark for evaluating in the modeling are evaluated and the results of several valid algorithms have been compared. The results indicate the high efficiency of the proposed algorithm in comparison with other algorithms.
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