Supply chain complexity and risk mitigation – A hybrid optimization–simulation model
针对加拿大新小麦分级制度下的质量检测问题，构建混合优化-仿真模型，寻找成本高效的品种检测策略，并通过敏感性分析验证现有策略的有效性。
With food safety a growing concern in agriculture, the structure and management of agricultural supply chains has become a significant policy issue. In turn, agricultural supply chains are often analytically complex, characterized by feedback and time sensitive, often random parameters. Modern commodity chains such as wheat handling in Canada are no exception. Recently, the Canadian government classes of wheat, replacing it by a new wheat segregation system that relies on trust and self-declaration of wheat type by individual farmers. To maintain food safety as well as operate cost-effectively in this new trust-based system, wheat handlers may be forced to develop a set of contamination testing strategies to maintain historical wheat quality and consistency. In contrast to much of the extant literature, this research builds a hybrid optimization-simulation model representing the new Canadian wheat supply chain, with the goal of identifying cost efficient varietal testing strategies. After solving for a base scenario, sensitivity analysis is conducted on key variables that influence wheat quality testing strategies. Our results validate the utility of currently employed wheat quality testing strategies in the Canadian supply chain.