A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain

Paul, SK; Sarker, R; Essam, D; Lee, PTW

A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain

Paul, SK

Sarker, R Essam, D Lee, PTW

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Publication Type:: Journal Article
Citation:: Annals of Operations Research, 2019, 280 (1-2), pp. 299 - 335
Issue Date:: 2019-09-15

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Field	Value	Language
dc.contributor.author	Paul, SK https://orcid.org/0000-0001-9523-179X	en_US
dc.contributor.author	Sarker, R	en_US
dc.contributor.author	Essam, D	en_US
dc.contributor.author	Lee, PTW	en_US
dc.date.available	2020-05-25T19:04:59Z
dc.date.issued	2019-09-15	en_US
dc.identifier.citation	Annals of Operations Research, 2019, 280 (1-2), pp. 299 - 335	en_US
dc.identifier.issn	0254-5330	en_US
dc.identifier.uri	http://hdl.handle.net/10453/132831
dc.description.abstract	© 2019, Springer Science+Business Media, LLC, part of Springer Nature. This paper aims to develop a recovery planning approach in a three-tier manufacturing supply chain, which has a single supplier, manufacturer, and retailer under an imperfect production environment, in which we consider three types of sudden disturbances: demand fluctuation, and disruptions to production and raw material supply, which are not known in advance. Firstly, a mathematical model is developed for generating an ideal plan under imperfect production for a finite planning horizon while maximizing total profit, and then we re-formulate the model to generate the recovery plan after happening of each sudden disturbance. Considering the high commercial cost and computational intensity and complexity of this problem, we propose an efficient heuristic, to obtain a recovery plan, for each disturbance type, for a finite future period, after the occurrence of a disturbance. The heuristic solutions are compared with a standard solution technique for a considerable number of random test instances, which demonstrates the trustworthy performance of the developed heuristics. We also develop another heuristic for managing the combined effects of multiple sudden disturbances in a period. Finally, a simulation approach is proposed to investigate the effects of different types of disturbance events generated randomly. We present several numerical examples and random experiments to explicate the benefits of our developed approaches. Results reveal that in the event of sudden disturbances, the proposed mathematical and heuristic approaches are capable of generating recovery plans accurately and consistently.	en_US
dc.relation.ispartof	Annals of Operations Research	en_US
dc.relation.isbasedon	10.1007/s10479-019-03251-w	en_US
dc.subject.classification	Operations Research	en_US
dc.title	A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain	en_US
dc.type	Journal Article
utslib.citation.volume	1-2	en_US
utslib.citation.volume	280	en_US
utslib.for	1503 Business and Management	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	15 Commerce, Management, Tourism and Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Management Discipline
utslib.copyright.status	open_access	*
pubs.issue	1-2	en_US
pubs.publication-status	Published	en_US
pubs.volume	280	en_US

Abstract:

© 2019, Springer Science+Business Media, LLC, part of Springer Nature. This paper aims to develop a recovery planning approach in a three-tier manufacturing supply chain, which has a single supplier, manufacturer, and retailer under an imperfect production environment, in which we consider three types of sudden disturbances: demand fluctuation, and disruptions to production and raw material supply, which are not known in advance. Firstly, a mathematical model is developed for generating an ideal plan under imperfect production for a finite planning horizon while maximizing total profit, and then we re-formulate the model to generate the recovery plan after happening of each sudden disturbance. Considering the high commercial cost and computational intensity and complexity of this problem, we propose an efficient heuristic, to obtain a recovery plan, for each disturbance type, for a finite future period, after the occurrence of a disturbance. The heuristic solutions are compared with a standard solution technique for a considerable number of random test instances, which demonstrates the trustworthy performance of the developed heuristics. We also develop another heuristic for managing the combined effects of multiple sudden disturbances in a period. Finally, a simulation approach is proposed to investigate the effects of different types of disturbance events generated randomly. We present several numerical examples and random experiments to explicate the benefits of our developed approaches. Results reveal that in the event of sudden disturbances, the proposed mathematical and heuristic approaches are capable of generating recovery plans accurately and consistently.

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http://hdl.handle.net/10453/132831