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Xanadu Farms: Weathering the Uncertainty
內容大綱
In March 2023, two strawberry producers in Ontario, Canada had to decide how many acres to plant with each of four strawberry varieties at Xanadu Farms. They had committed to providing 275,000 pounds of berries to a local independent grocery chain and also required some of their berry crop to make strawberry preserves. Complicating this decision was the impact that weather had on the yield of each type of berry. If the weather reduced the yield, the two producers would need to make up for the loss by sourcing berries from several nearby farmers. However, if the weather was favourable, they would be able to sell any excess berries at their own storefront. What current decision should the two strawberry producers make to ensure they achieve the best outcome one year later?
學習目標
This exercise can be used in an undergraduate- or graduate-level business analytics course that has a component on prescriptive analytics or optimization. Students should be familiar with formulating deterministic linear programming problems and solving them with either Microsoft Excel or a commercial optimization solver. This exercise provides students an opportunity to develop optimization modelling skills applied in a situation that is ripe with uncertainty. After working through the exercise and assignment questions, students will be able to<ul><li>model a two-stage stochastic optimization model with recourse;</li><li>implement and solve the optimization formulation in Microsoft Excel;</li><li>calculate the expected value of perfect information and the value of the stochastic solution; and</li><li>interpret the model results and provide meaningful managerial insights.</li><li>