Mixed Truncated Random Variable Fitting with the GLD, and Applications in Insurance and Inventory Management

2010 ◽  
pp. 1145-1169
Keyword(s):  
Inventory Management ◽  
Random Variable

The economic order quantity model with inspection policy of zero-defect single sampling

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdi Nakhaeinejad
Keyword(s):  
Sample Size ◽  
Inventory Management ◽  
Optimal Solution ◽  
Random Variable ◽  
Solution Procedure ◽  
Order Quantity ◽  
Content Type ◽  
Numerical Examples ◽  
Proposed Model ◽  
Inspection Policy

PurposeThis paper proposes a new inventory model with inspection policy because in practice the received orders may contain non- conforming (NC) items. So, a buyer who receive an order from a supplier should use an inspection policy.Design/methodology/approachThe inspection policy is assumed to be zero-defect single sampling. Under this policy a lot is accepted only if no defect has been identified in the inspected sample. The fraction of NC is assumed to be a random variable following a Binomial distribution and the number of NC items detected by inspection assumed to be a random variable, which follows a hypergeometric distribution. Order quantity and sample size are the two decision variables. A solution procedure is presented for the proposed model. The proposed procedure presents the optimal solution.FindingsNumerical examples presented to illustrate the procedure outlined for the proposed model and its applicability. The results of numerical examples and comparing them with traditional EOQ model reveal that by the proposed model, the buyer could reduce total cost that shows the efficiency and validity of the proposed model.Originality/valueThe novelty of this paper is the new proposed model that considers inspection policy in inventory management. The proposed model determines sample size as well as order quantity to consider both subject of inventory management and quality control, simultaneously.

Generation of Correlated Logistic-Normal Random Variates for Medical Decision Trees

1998 ◽  
Vol 37 (03) ◽  
pp. 235-238 ◽  
Author(s):  
M. El-Taha ◽  
D. E. Clark
Keyword(s):  
Monte Carlo ◽  
Decision Trees ◽  
Computer Algebra ◽  
Taylor Series ◽  
Computer Algebra System ◽  
Random Variable ◽  
Monte Carlo Analysis ◽  
Normal Random Variable ◽  
Medical Decision ◽  
Theoretical Results

AbstractA Logistic-Normal random variable (Y) is obtained from a Normal random variable (X) by the relation Y = (ex)/(1 + ex). In Monte-Carlo analysis of decision trees, Logistic-Normal random variates may be used to model the branching probabilities. In some cases, the probabilities to be modeled may not be independent, and a method for generating correlated Logistic-Normal random variates would be useful. A technique for generating correlated Normal random variates has been previously described. Using Taylor Series approximations and the algebraic definitions of variance and covariance, we describe methods for estimating the means, variances, and covariances of Normal random variates which, after translation using the above formula, will result in Logistic-Normal random variates having approximately the desired means, variances, and covariances. Multiple simulations of the method using the Mathematica computer algebra system show satisfactory agreement with the theoretical results.

277. EH&S Inventory Management Program on the Web

2002 ◽  
Author(s):  
W. Jancuk ◽  
D. Nargis ◽  
R. Collipi
Keyword(s):  
Inventory Management ◽  
Management Program ◽  
The Web

Inventory Reduction by Applying Inventory Management Tools of a Selected Tannery Factory

2015 ◽  
Vol 6 (1) ◽  
pp. 204-210
Author(s):  
Azim Mohammad Mohammad ◽  
Shibbir Ahmad ◽  
Mohammad Iqbal ◽  
Md. Alauddin
Keyword(s):  
Inventory Management ◽  
Management Tools

An Analytical Study on Inventory Management Practices For an Auto Component Major in Chennai City

2011 ◽  
Vol 3 (8) ◽  
pp. 386-389
Author(s):  
Dr. K. Sadasivan Dr. K. Sadasivan ◽  
◽  
S. Kavitha S. Kavitha ◽  
Britto A Britto A
Keyword(s):  
Inventory Management ◽  
Analytical Study ◽  
Management Practices ◽  
Chennai City ◽  
Auto Component
Sign in / Sign up

Export Citation Format

Share Document