Design of Decision Support System to Forecast Demand for Dynamic Network Design Based on Uncertainty and its Impact on Economic Justification
Subject Areas : Financial engineeringMohammad Mokhtari 1 , Aboutorab Alirezaei 2 , Hassan Javanshir 3 , Mahmoud Modiri 4
1 - Department of Industrial Management, Faculty of Management,, South Tehran Branch, islamic Azad University, tehran, iran
2 - Industrial Management, Faculty of Management, South Tehran Branch, Islamic Azad University,Tehran, Iran.
3 - Department of Industries, Faculty of Industries, South Tehran Branch, Islamic Azad University, Tehran, Iran.
4 - Department of Industrial Management, Faculty of Management, South Tehran Branch, Islamic Azad University, Tehran, Iran.
Keywords: Uncertainty, Network design, Decision support system, forecasting, Robustness,
Abstract :
Minimize supply chain costs as one of the essential issues in support activities such as financial planning systems,How to manage supply chain A set of ways to integrate Effective suppliers, manufacturers, warehouses and stores used to minimize total supply chain costs and meet customer service needs with a high level of service. In this study, the design of a robust cement supply chain dynamic network model was designed to reduce supply chain management costs after a crisis. Principal and efficient design of cement grid infrastructures, given the strong demand fluctuations at different times of the year, can significantly reduce financial costs on the one hand and reduce the potential for high-speed, high-cost corruption by correct prediction. Other leads.From the following tool The nose has been analyzed using artificial neural networks. The purpose of this study is to use artificial intelligence methodologies such as Grid Clustering, Subtractive Partitioning, FCM to explore fundamental and technical patterns and relationships in historical data. Used. To this end, a genetically-based inference fuzzy multilayer fuzzy neural network is introduced to prevent technical and economic unpredictability. The basic model of this paper presented by the researcher is a robust and multi-periodic planning for multi-product state under uncertainty.
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