We present a stochastic optimisation model that can be used to design a resilient supply chain operating under random disruptions. The model aims to determine sourcing and network design decisions that minimise the expected total cost while ensuring that the minimum customer service level is achieved. The proposed model incorporates several resilience strategies including multiple sourcing, multiple transport routes, considering backup suppliers, adding extra production capacities, as well as lateral transshipment and direct shipment. A multi-cut L-shaped solution approach is developed to solve the proposed model. Data from a real case problem in the paint industry is utilised to test the model and solution approach. Important managerial insights are obtained from the case study. Our analyses focus on (1) exploring the relationship between supply chain cost and customer service level, (2) examining the impacts of different types of disruptions on the total cost, (3) evaluating the utility of resilience strategies, (4) investigating the benefits of the proposed solution approach to solve problems of different sizes and (5) benchmarking the performance of the proposed stochastic programming approach.

中文翻译：

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一种用于弹性和响应性供应链网络设计的多切割 L 形方法

我们提出了一个随机优化模型，可用于设计在随机中断下运行的弹性供应链。该模型旨在确定在确保实现最低客户服务水平的同时，最大限度地降低预期总成本的采购和网络设计决策。提议的模型结合了多种弹性策略，包括多采购、多运输路线、考虑备用供应商、增加额外的生产能力以及横向转运和直接运输。开发了一种多切割 L 形求解方法来求解所提出的模型。来自涂料行业真实案例问题的数据用于测试模型和解决方案。从案例研究中获得了重要的管理见解。