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Title Effectiveness of lead-time management in a sustainable supply chain under intuitionistic fuzzy environment: analytical and metaheuristic optimisation approach
ID_Doc 74826
Authors Karthick, B; Uthayakumar, R
Title Effectiveness of lead-time management in a sustainable supply chain under intuitionistic fuzzy environment: analytical and metaheuristic optimisation approach
Year 2023
Published International Journal Of Systems Science-Operations & Logistics, 10, 1
DOI 10.1080/23302674.2023.2252325
Abstract This paper investigates a two-echelon disrupted supply chain model that includes energy consumption and carbon emissions. During the global crisis caused by the previous pandemic, demand for essential goods increased, and as a consequence, businesses struggled to produce and ship goods to buyers. In this situation, it is crucial to shorten the lead time in order to deliver the goods to the buyer as soon as possible. Based on this, this paper analyses lead time into three components, namely: set-up time, transport time and production time. Additionally, Vendor Managed Inventory-Consignment Stock policy is adopted to increase business connectivity between supply chain players and reduce inventory costs. In such a case, this work addresses the ambiguity using an intuitionistic fuzzy number for unexpected demand. Therefore, the key objective of this work is to obtain the minimum total cost of a disrupted supply chain with respect to three different optimization techniques under triangular intuitionistic fuzzy demand. So far, no such inventory model has been developed with the aim of reducing set-up and transportation time in an intuitionistic fuzzy environment. Also, numerical experiments and sensitivity analysis are performed to test the performance of the proposed model. Finally, administrative insights and conclusions are presented.
Author Keywords Consignment stock; uncertain demand; setup time; transportation time; carbon emission
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:001068310500001
WoS Category Engineering, Industrial; Operations Research & Management Science
Research Area Engineering; Operations Research & Management Science
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