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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Finally, the accuracy of the asymptotic expansion is examined with Monte Carlo simulation method.
📌 3 Key Takeaways
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Objective & Hypothesis:In this study, asymptotic expansion for ergodic distribution of an inventory control model of type s, S with generalized beta interference of chance is obtained, when S − s → ∞.
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Key Findings & Data:Moreover, weak convergence theorem is proved for ergodic distribution.
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Conclusion & Impact:Finally, the accuracy of the asymptotic expansion is examined with Monte Carlo simulation method.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Inventory model of type s · renewal-reward process · generalized betadistribution
Abstract
In this study, asymptotic expansion for ergodic distribution of an inventory control model of type s, S with generalized beta interference of chance is obtained, when S − s → ∞. Moreover, weak convergence theorem is proved for ergodic distribution. Finally, the accuracy of the asymptotic expansion is examined with Monte Carlo simulation method.
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Cite This Article
Khaniyev, T., Aksop, C. (2011). ASYMPTOTIC RESULTS FOR AN INVENTORY MODEL OF TYPE s, S WITH A GENERALIZED BETA INTERFERENCE OF CHANCE. TWMS Journal of Applied and Engineering Mathematics, Volume: 01 Issue: 2. https://ajindex.com/articles/1604706