Managing uncertainty is an important topic in production planning. Stochastic programming is a method to cope with uncertainty that can directly integrate the uncertainty in the modeling to solve for an optimal result as well as outputs that provide the human decision-maker with valuable insights about the production planning problem. While the computational intensity is addressed through recent advances in solution approaches and better commercial solvers, the communication and interpretation issue is rarely touched. This paper aims to encourage the implementation of the stochastic programming method by proposing an approach to communicate the values of stochastic programming to the human decision-maker. The approach is applied to a numerical example of a Fast Moving Consumer Goods (FMCG) manufacturer of tomato ketchup tactical production planning where demand is uncertain.
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Managing uncertainty is an important topic in production planning. Stochastic programming is a method to cope with uncertainty that can directly integrate the uncertainty in the modeling to solve for an optimal result as well as outputs that provide the human decision-maker with valuable insights about the production planning problem. While the computational intensity is addressed through recent advances in solution approaches and better commercial solvers, the communication and interpretation i...
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