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Optimizing multi-channel procurement planning under disruption risks
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DOI：10.1016/j.ijpe.2024.109346.png)
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Procurement plays a vital role in supply chain management, which directly affects the production, delivery, and reputation of enterprises. This paper investigates the multi-channel procurement planning problem (MCPP-R) considering the impact of disruption risk, uncertain demand and spot-market price. To meet the customer demand, the buyer can make purchases by signing a long-term contract with the primary supplier (PS), which offers certain advantages in price but may be susceptible to disruption risks. Alternatively, the buyer can enter into an option contract to retain the right to purchase from a backup supplier (BS). Additionally, the buyer can also purchase from the spot market with uncertain prices. During the procurement process, the buyer needs to decide the quantity to order from the PS and the quantity to reserve from the BS first, and then decide the quantities to reserve from a BS and the spot market respectively when the customer demand realization and spot-market price emerge. The MCPP-R is to find the optimal procurement portfolio solution with the minimum expected total procurement cost, formulated as a two-stage stochastic programming model. Due to the non-convex and non- continuous nature, the MCPP-R model is solved optimally by transforming equivalently into a shortest-path problem (SPP) with constraints. The solution method does not have specific requirements for the distribution of uncertain demand and spot-market price. We conduct extensive numerical experiments to analyze the impact of risk and uncertainty in demand and spot-market price on the procurement plan. The experimental analysis indicates that BS plays a crucial role in most cases, particularly with high disruption probability or high spot- market price.
Keyword:
Disruption risk
Uncertainty
Multiple channels procurement
Procurement plan
Shortest-path problem
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10
论文数:
8.1K
被引数:
3.6W
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Resilient supplier selection and optimal order allocation under disruption risks中断风险下的弹性供应商选择和最优订单分配
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