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Optimal Replenishment Policy for Ameliorating Item with Shortages under Inflation and Time Value of Money using Genetic Algorithm

by S.R. Singh, Tarun Kumar, C. B. Gupta
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 27 - Number 1
Year of Publication: 2011
Authors: S.R. Singh, Tarun Kumar, C. B. Gupta
10.5120/3269-4431

S.R. Singh, Tarun Kumar, C. B. Gupta . Optimal Replenishment Policy for Ameliorating Item with Shortages under Inflation and Time Value of Money using Genetic Algorithm. International Journal of Computer Applications. 27, 1 ( August 2011), 5-17. DOI=10.5120/3269-4431

@article{ 10.5120/3269-4431,
author = { S.R. Singh, Tarun Kumar, C. B. Gupta },
title = { Optimal Replenishment Policy for Ameliorating Item with Shortages under Inflation and Time Value of Money using Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 27 },
number = { 1 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 5-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume27/number1/3269-4431/ },
doi = { 10.5120/3269-4431 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:12:39.176784+05:30
%A S.R. Singh
%A Tarun Kumar
%A C. B. Gupta
%T Optimal Replenishment Policy for Ameliorating Item with Shortages under Inflation and Time Value of Money using Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 27
%N 1
%P 5-17
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The implementation of supply chain has to reduce the total cost of system, but generally each component of a supply chain tries to find the best policy for its company and consequently tries to find a local optimum. Knowing that the sum of local optimum cannot constitute the global optimum, it is necessary to consider all costs of system simultaneously to find the optimal replenishment policy for all the components of a supply chain. Demand rate of the item is assumed to be a function of time known as ramp type function. Shortages are permitted and partially back-ordered. The back-ordering fraction is taken to be decreasing function of waiting time. We consider inflation and apply discounted cash flow in the problem analysis. Total cost of the system is formulated and optimal replenishment policy is derived, keeping in view the above factors of the system. We use Genetic Algorithm (GA) to solve the models. A numerical example and sensitivity analysis is shown to illustrate the models.

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Index Terms

Computer Science
Information Sciences

Keywords

Replenishment policy ramp type demand amelioration items Genetic algorithm

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