The Applications of the Modified Generalized Gamma Distribution in Inventory Control

Faculty Commerce Year: 2011
Type of Publication: ZU Hosted Pages: 1699 - 1712
Authors:
Mohamed Elsayed Ahmed Mead
Journal: Int. J. Contemp. Math. Sciences Bulgaria Volume: Vol. 6
Keywords : , Applications , , Modified Generalized Gamma Distribution , Inventory Control    
Abstract:
The main objective of this thesis is the determination of the protection lost sales (i.e., the probability of not going out of stock) and the potential lost sales (i.e., the unsatisfied demand) when the lead time demand has the modified
    
     
 
       

Author Related Publications

  • Mohamed Elsayed Ahmed Mead, "A New Generalization of Burr XII Distribution", Pakistan, 2014 More
  • Mohamed Elsayed Ahmed Mead, "An Extended Pareto Distribution", Pakistan, 2014 More
  • Mohamed Elsayed Ahmed Mead, "A note on Kumaraswamy Fréchet distribution", Australia, 2014 More
  • Mohamed Elsayed Ahmed Mead, "STATISTICAL PROPERTIES FOR THE GENERALIZED COMPOUND GAMMA DISTRIBUTION", كلية التجارة - جامعة بنها, 2008 More
  • Mohamed Elsayed Ahmed Mead, "The Applications of the Generalized Beta II Distribution in Inventory Control", Austuralia, 2013 More

Department Related Publications

  • Hatem Elsayed Abdelwahied Semary, "أثر زيادة تركيزات ملوثات الهواء فى المناطق الحضرية على صحة الأطفال", جامعة الدول العربية - مصر, 2015 More
  • Hatem Elsayed Abdelwahied Semary, "الرضا الوظيفى لأعضاء هيئة التدريس والهيئة المعاونة والعاملين بكلية طب قصر العينى – جامعة القاهرة", جامعة القاهرة، مصر, 2016 More
  • Mazen Mohamed Abd ulrahman, "Inference for Weibull distribution under adaptive Type-I progressive hybrid censored competing risks data", Taylor and Francis, 2017 More
  • Hatem Elsayed Abdelwahied Semary, "Bayes Inference in Multiple Step–Stress Accelerated Life Tests for the Generalized Exponential Distribution with Type–I Censoring", VENEZUELA, 2020 More
  • Hassan Mohamed Ali Hessien, "معالجة مشكلة الازدواج الخطى فى الانحدار اللوجستى Treatment of Multicollinearity in the Logistic Regression Model.", 2024 More
Tweet