z-logo
open-access-imgOpen Access
Continuous review inventory models under time value of money and crashable lead time consideration
Author(s) -
Kuo-Chen Hung
Publication year - 2011
Publication title -
yugoslav journal of operations research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.221
H-Index - 21
eISSN - 1820-743X
pISSN - 0354-0243
DOI - 10.2298/yjor1102293h
Subject(s) - time value of money , lead time , stock (firearms) , computer science , crash , asset (computer security) , sensitivity (control systems) , value (mathematics) , order (exchange) , econometrics , mathematical optimization , operations research , mathematical economics , mathematics , economics , finance , operations management , mechanical engineering , machine learning , engineering , programming language , computer security , electronic engineering
A stock is an asset if it can react to economic and seasonal influences in the management of the current assets. The financial manager must calculate the input of funds to the stock intelligently and the amount of money cycled through stocks, taking into account the time factors in the future. The purpose of this paper is to propose an inventory model considering issues of crash cost and current value. The sensitivity analysis of each parameter, in this research, differs from the traditional approach. We utilize a course of deduction with sound mathematics to develop several lemmas and one theorem to estimate optimal solutions. This study first tries to find the optimal order quantity at all lengths of lead time with components crashed at their minimum duration. Second, a simple method to locate the optimal solution unlike traditional sensitivity analysis is developed. Finally, some numerical examples are given to illustrate all lemmas and the theorem in the solution algorithm

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom