Improving on Shadow Price Information for Identifying Critical Farm Machinery
提出一种在线性规划中识别关键农业机械的方法，通过技术系数敏感性分析公式克服直接使用影子价格的问题，案例显示识别机械调整收益的误差小于10%。
Abstract A method is presented for identifying critical farm machinery in a linear programming context. The method uses a technical coefficient sensitivity analysis formula that overcomes problems associated with direct use of shadow prices for critical machinery identification. Case studies show the formula identifies the benefits of altering machinery generally with less than 10% error.