A combined approach for modeling multi-echelon multi-period decentralized supply chain

Haque, M; Paul, SK; Sarker, R; Essam, D

A combined approach for modeling multi-echelon multi-period decentralized supply chain

Haque, M Paul, SK Sarker, R Essam, D

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Publisher:: Springer Science and Business Media LLC
Publication Type:: Journal Article
Citation:: Annals of Operations Research, 2022, 315, (2), pp. 1665-1702
Issue Date:: 2022-08

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Field	Value	Language
dc.contributor.author	Haque, M
dc.contributor.author	Paul, SK
dc.contributor.author	Sarker, R
dc.contributor.author	Essam, D
dc.date.accessioned	2022-10-10T02:40:53Z
dc.date.available	2021-05-12
dc.date.available	2022-10-10T02:40:53Z
dc.date.issued	2022-08
dc.identifier.citation	Annals of Operations Research, 2022, 315, (2), pp. 1665-1702
dc.identifier.issn	0254-5330
dc.identifier.issn	1572-9338
dc.identifier.uri	http://hdl.handle.net/10453/162424
dc.description.abstract	In this paper, a multi-echelon, multi-period, decentralized supply chain (SC) with a single manufacturer, single distributor and single retailer is considered. For this setting, a two-phase planning approach combining centralized and decentralized decision-making processes is proposed, in which the first-phase planning is a coordinated centralized controlled, and the second-phase planning is viewed as independent decentralized decision-making for individual entities. This research focuses on the independence and equally powerful behavior of the individual entities with the aim of achieving the maximum profit for each stage. A mathematical model for total SC coordination as a first-phase planning problem and separate ones for each of the independent members with their individual objectives and constraints as second-phase planning problems are developed. We introduce a new solution approach using a goal programming technique in which a target or goal value is set for each independent decision problem to ensure that it obtains a near value for its individual optimum profit, with a numerical analysis presented to explain the results. Moreover, the proposed two-phase model is compared with a single-phase approach in which all stages are considered dependent on each other as parts of a centralized SC. The results prove that the combined two-phase planning method for a decentralized SC network is more realistic and effective than a traditional single-phase one.
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/s10479-021-04121-0
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	01 Mathematical Sciences, 08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services
dc.subject.classification	Operations Research
dc.title	A combined approach for modeling multi-echelon multi-period decentralized supply chain
dc.type	Journal Article
utslib.citation.volume	315
utslib.location.activity	United States
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
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	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2022-10-10T02:40:49Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	315
utslib.citation.issue	2

Abstract:

In this paper, a multi-echelon, multi-period, decentralized supply chain (SC) with a single manufacturer, single distributor and single retailer is considered. For this setting, a two-phase planning approach combining centralized and decentralized decision-making processes is proposed, in which the first-phase planning is a coordinated centralized controlled, and the second-phase planning is viewed as independent decentralized decision-making for individual entities. This research focuses on the independence and equally powerful behavior of the individual entities with the aim of achieving the maximum profit for each stage. A mathematical model for total SC coordination as a first-phase planning problem and separate ones for each of the independent members with their individual objectives and constraints as second-phase planning problems are developed. We introduce a new solution approach using a goal programming technique in which a target or goal value is set for each independent decision problem to ensure that it obtains a near value for its individual optimum profit, with a numerical analysis presented to explain the results. Moreover, the proposed two-phase model is compared with a single-phase approach in which all stages are considered dependent on each other as parts of a centralized SC. The results prove that the combined two-phase planning method for a decentralized SC network is more realistic and effective than a traditional single-phase one.

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http://hdl.handle.net/10453/162424