Optimal supplier testing and tolerance strategies for genetically modified (GM) wheat
开发了一个随机优化模型，用于确定转基因与非转基因小麦双营销出口供应链中的最优检测策略、成本和风险，发现检测和分离可以以较低成本和风险实现。
Abstract A stochastic optimization model was developed to determine optimal testing strategies, costs, and risks for dual marketing of genetically modified (GM) and non‐GM wheat in an export supply chain. The optimal testing strategy is derived that minimizes disutility of additional system costs due to testing and quality loss. Cost components were estimated including those related to testing, quality loss, and a risk premium to induce shippers to undertake dual marketing as opposed to handling only non‐GM crops. Uncertainties were incorporated for adventitious presence and commingling, variety declaration, and test accuracy. Sensitivities were performed for effects of variety risks and declaration, penalty differentials, buyer tolerances, risk aversion, and GM adoption. Results indicate testing and segregation can be performed at a relatively low cost and risk to buyers.