Inventory planning under supplier uncertainty in a two-level supply chain

被引:6
作者
Yassine, Noura [1 ]
机构
[1] Beirut Arab Univ, Beirut, Lebanon
关键词
Inventory control; Supply chain; Uncertainty; Supplier selection; PREDICTIVE ANALYTICS; BIG DATA; DISRUPTION; PERFORMANCE; RESILIENCE; MANAGEMENT; DEMAND; MODEL;
D O I
10.1108/IJLM-02-2021-0104
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Purpose Due to uncertainty in supply chains caused by the coronavirus disease 2019 (COVID-19), organizations are adjusting their supply chain design to address challenges faced during the pandemic. To safeguard their operations against disruption in order quantities, supply chain members have been looking for alternate suppliers. This paper considers a two-level supply chain consisting of a manufacturer and two suppliers of a certain type of components required for the production of a finished product. The primary supplier (supplier A) is unreliable, in the sense that the quantity delivered is usually less than the ordered quantity. The proportion of the ordered quantity delivered by supplier A is a random variable with a known probability distribution. The secondary supplier (supplier B) always delivers the order in its entirety at a higher cost and can respond instantaneously. In order for supplier B to respond instantaneously, the manufacturer is required to reserve a certain quantity at an additional cost. Once the quantity received from the main supplier is observed, the manufacturer may place an order not exceeding the reserved quantity. Design/methodology/approach A mathematical model describing the production/inventory situation of the supply chain is formulated. The model allows the determination of the manufacturer's optimal ordering policy. Findings An expression for the expected total cost per unit time function is derived. The optimal solution is determined by solving a system of nonlinear equations obtained by minimizing the expected total cost function. Practical implications The proposed model can be used by supply chain managers aiming at identifying various ways of handling the uncertainty in the flow of supplies across the chain. Originality/value This proposed model addresses a gap in the production/inventory literature.
引用
收藏
页码:497 / 516
页数:20
相关论文
共 65 条
[1]   Supply chain resilience: a dynamic and multidimensional approach [J].
Adobor, Henry ;
McMullen, Ronald S. .
INTERNATIONAL JOURNAL OF LOGISTICS MANAGEMENT, 2018, 29 (04) :1451-1471
[2]   Vulnerable options in supply chains: Effects of supplier competition [J].
Babich, Volodymyr .
NAVAL RESEARCH LOGISTICS, 2006, 53 (07) :656-673
[3]   A CONTINGENT RESOURCE-BASED PERSPECTIVE OF SUPPLY CHAIN RESILIENCE AND ROBUSTNESS [J].
Brandon-Jones, Emma ;
Squire, Brian ;
Autry, Chad W. ;
Petersen, Kenneth J. .
JOURNAL OF SUPPLY CHAIN MANAGEMENT, 2014, 50 (03) :55-73
[4]   Outsourcing strategy and production disruption of supply chain with demand and capacity allocation uncertainties [J].
Chen, Kebing ;
Xiao, Tiaojun .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2015, 170 :243-257
[5]   Innovative "Bring-Service-Near-Your-Home" operations under Corona-Virus (COVID-19/SARS-CoV-2) outbreak: Can logistics become the Messiah? [J].
Choi, Tsan-Ming .
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2020, 140
[6]   The importance of decoupling recurrent and disruption risks in a supply chain [J].
Chopra, Sunil ;
Reinhardt, Gilles ;
Mohan, Usha .
NAVAL RESEARCH LOGISTICS, 2007, 54 (05) :544-555
[7]   COVID-19 pandemic related supply chain studies: A systematic review [J].
Chowdhury, Priyabrata ;
Paul, Sanjoy Kumar ;
Kaisar, Shahriar ;
Moktadir, Md. Abdul .
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2021, 148
[8]   How simulation modelling can help reduce the impact of COVID-19 [J].
Currie, Christine S. M. ;
Fowler, John W. ;
Kotiadis, Kathy ;
Monks, Thomas ;
Onggo, Bhakti Stephan ;
Robertson, Duncan A. ;
Tako, Antuela A. .
JOURNAL OF SIMULATION, 2020, 14 (02) :83-97
[9]   A production inventory supply chain model with partial backordering and disruption under triangular linguistic dense fuzzy lock set approach [J].
De, Sujit Kumar ;
Mahata, Gour Chandra .
SOFT COMPUTING, 2020, 24 (07) :5053-5069
[10]  
Dubey Rameshwar, 2015, Industrial and Commercial Training, V47, P86, DOI 10.1108/ICT-08-2014-0052