An inventory model for a three-stage supply chain with random capacities considering disruptions and supplier reliability

Islam, MT; Azeem, A; Jabir, M; Paul, A; Paul, SK

An inventory model for a three-stage supply chain with random capacities considering disruptions and supplier reliability

Islam, MT Azeem, A Jabir, M Paul, A Paul, SK

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Publisher:: Springer Science and Business Media LLC
Publication Type:: Journal Article
Citation:: Annals of Operations Research, 2020, pp. 1-26
Issue Date:: 2020-05

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Field	Value	Language
dc.contributor.author	Islam, MT
dc.contributor.author	Azeem, A
dc.contributor.author	Jabir, M
dc.contributor.author	Paul, A
dc.contributor.author	Paul, SK
dc.date.accessioned	2020-08-13T01:24:19Z
dc.date.available	2020-08-13T01:24:19Z
dc.date.issued	2020-05
dc.identifier.citation	Annals of Operations Research, 2020, pp. 1-26
dc.identifier.issn	0254-5330
dc.identifier.issn	1572-9338
dc.identifier.uri	http://hdl.handle.net/10453/142084
dc.description.abstract	This study develops an inventory model to solve the problems of supply uncertainty in response to demand which follows a Poisson distribution. A positive aspect of this model is the consideration of random inventory, delivery capacities and supplier's reliability. Additionally, we assume supplier capacity follows an exponential distribution. This inventory model addresses the problem of a manufacturer having an imperfect production system with single supplier and single retailer and considers the quantity of product (Q), reorder points (r) and reliability factors (n) as the decision variables. The main contribution of our study is that we consider supplier may not be able to deliver the exact amount all the time a manufacturer needed. We also consider that the demand and the time interval between successive availability and unavailability of supplier and retailer follows a probability distribution. We use a genetic algorithm to find the optimal solution and compare the results with those obtained from simulated annealing algorithm. Findings reveal the optimal value of the decision variables to maximize the average profit in each cycle. Moreover, a sensitivity analysis was carried out to increase the understanding of the developed model. The methodology used in this study will help manufacturers to have a better understanding of the situation through the joint consideration of disruption of both the supplier and retailer integrated with random capacity and reliability.
dc.format	Print-Electronic
dc.language	en
dc.publisher	Springer Science and Business Media LLC
dc.relation.ispartof	Annals of Operations Research
dc.relation.isbasedon	10.1007/s10479-020-03639-z
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	01 Mathematical Sciences, 08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services
dc.subject.classification	Operations Research
dc.title	An inventory model for a three-stage supply chain with random capacities considering disruptions and supplier reliability
dc.type	Journal Article
utslib.location.activity	United States
utslib.for	1503 Business and Management
utslib.for	01 Mathematical Sciences
utslib.for	08 Information and Computing Sciences
utslib.for	15 Commerce, Management, Tourism and Services
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Management Discipline
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2020-08-13T01:24:11Z
pubs.publication-status	Published

Abstract:

This study develops an inventory model to solve the problems of supply uncertainty in response to demand which follows a Poisson distribution. A positive aspect of this model is the consideration of random inventory, delivery capacities and supplier's reliability. Additionally, we assume supplier capacity follows an exponential distribution. This inventory model addresses the problem of a manufacturer having an imperfect production system with single supplier and single retailer and considers the quantity of product (Q), reorder points (r) and reliability factors (n) as the decision variables. The main contribution of our study is that we consider supplier may not be able to deliver the exact amount all the time a manufacturer needed. We also consider that the demand and the time interval between successive availability and unavailability of supplier and retailer follows a probability distribution. We use a genetic algorithm to find the optimal solution and compare the results with those obtained from simulated annealing algorithm. Findings reveal the optimal value of the decision variables to maximize the average profit in each cycle. Moreover, a sensitivity analysis was carried out to increase the understanding of the developed model. The methodology used in this study will help manufacturers to have a better understanding of the situation through the joint consideration of disruption of both the supplier and retailer integrated with random capacity and reliability.

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http://hdl.handle.net/10453/142084