A quality risk management problem: case of annual crop harvest scheduling
International Journal of Production Research
This paper presents a stochastic optimization model for the annual harvest scheduling problem of the farmers' entire cereal crop production at optimum maturity. Gathering the harvest represents an important stage for both agricultural cooperatives and individual farmers due to its high cost and considerable impact on seed quality and yield. The meteorological conditions represent the deciding factor that aects the harvest scheduling and progress. Using chance constrained programming, a mixed integer probabilistically constrained model is proposed, with a view to minimizing the risk of crop quality degradation under climate uncertainty with a safe condence level. The chance constrained optimization problem is tackled and solved via an equivalent linear mixed integer reformulation jointly with scenario based approaches. Moreover, a new concept of (1 - \alpha)- scenario pertinence is introduced in order to defy eciently the probabilistically constrained problem complexity and time limitations. From the practical standpoint, this study is aimed at helping an agricultural cooperative in decision making on crop quality risk management and harvest scheduling over a medium time horizon (10-15 time periods).