Joint Fuzzy Logic and Genetic Algorithm to Management of Cost-time-quality in Modern Milling units of Rasht County

Document Type : Research Paper


1 PhD Graduated, Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

2 Full Professor, Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran


Managing three indicators of quality, cost and time in rice production is important.Therefore, the purpose of this study was to achieve optimal layout of different methods with the lowest cost, minimum time and highest quality in the conversion process. For this purpose, all possible methods for each stage of the conversion process in the modern milling units were expressed and a series of fuzzy numbers was considered for them. Risk management was also done by applying fuzzy cutes from zero to one to investigate uncertainty. In the next step, the project management was adopted using the non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranked genetic algorithm (NRGA-II). Based on the results, the genetics algorithm (NSGA-II) showed better performance in comparison with genetic algorithm (NRGA-II) in solving this problem and finally, the lowest time, minimum cost and the highest quality in the specified conditions (α = 1) were founded 22.22 hours, 8088170 Rial and 62%, respectively.


Main Subjects

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