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An optimization-based approach for managing downstream logistic operations: A real application in pandemic outbreak conditions
Computers & Industrial Engineering ; 171:108495, 2022.
Article in English | ScienceDirect | ID: covidwho-1966433
ABSTRACT
One of the most destructive effects of pandemics and epidemics outbreak is the severe deficiency of basic goods needed by society, especially in underdeveloped and developing countries. Therefore, designing an efficient managerial model for making operative modifications in logistics networks beside the governmental financial support policies is considered as one of the most important managerial challenges in the critical situation of the prevalence of infectious diseases that is not investigated in the literature. In this paper, an optimization-based approach is developed to design the supply, production, and distribution channels of basic goods using the capacity of small and medium-sized enterprises (SMEs) under direct supervision of the government in order to increase both the agility and resilience of logistics networks. Since the NP-hardess of the discussed problem, an iterative two-step heuristic based on local search (ITbLS) is developed to solve the proposed problem. According to the numerical results, it can be observed that the proposed algorithm has a good performance to obtain near-optimal solutions for the case study. Moreover, the numerical analyses indicate that the percentage of the active capacity of suppliers, transportation fleet, SMEs, and distribution centers, is specifically dependent on the amount of demand and the number of the established SMEs. In general, managerial results of the proposed model make supply chains more efficient by exploiting the capacity of SMEs and improve the government finaical resources allocation to the private sector to supply basic goods in critical situations.
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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Language: English Journal: Computers & Industrial Engineering Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Language: English Journal: Computers & Industrial Engineering Year: 2022 Document Type: Article