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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
The well-known equilibrium algorithm is extended to find system optimization pattern for such multiproduct supply chainnetwork.
📌 3 Key Takeaways
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Objective & Hypothesis:In this paper, multiproduct supply chain network model is developed with system optimization perspective.
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Key Findings & Data:Each kind of products has an individual cost function and, at the same time,contributes to its own and other product's cost function in an individual way.
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Conclusion & Impact:The well-known equilibrium algorithm is extended to find system optimization pattern for such multiproduct supply chainnetwork.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In this paper, multiproduct supply chain network model is developed with system optimization perspective. Each kind of products has an individual cost function and, at the same time,contributes to its own and other product's cost function in an individual way. The well-known equilibrium algorithm is extended to find system optimization pattern for such multiproduct supply chainnetwork.
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Cite This Article
BOSTANABAD, M. S., MEHRİ-TEKMEH, J., MİRNİA, M., DEHKHARGHANİ, A. M. (2022). The system optimization perspective for multiproduct supply chain network. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), Cilt: 3 - Sayı: 2, 153–159. https://ajindex.com/articles/440734