Design of a neuro-fuzzy–regression expert system to estimate cost in a flexible jobshop automated manufacturing system |
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Authors: | Hamed Fazlollahtabar Nezam Mahdavi-Amiri |
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Affiliation: | 1. Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran 2. Faculty of Mathematical Sciences, Sharif University of Technology, Tehran, Iran
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Abstract: | We propose a cost estimation model based on a fuzzy rule backpropagation network, configuring the rules to estimate the cost under uncertainty. A multiple linear regression analysis is applied to analyze the rules and identify the effective rules for cost estimation. Then, using a dynamic programming approach, we determine the optimal path of the manufacturing network. Finally, an application of this model is illustrated through a numerical example showing the effectiveness of the proposed model for solving the cost estimation problem under uncertainty. |
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