

![0_image_0.png](0_image_0.png)

A smaller version of the above problem is designed with 4 stages, [5,4,4,3] states in each stage and hence 240 scenarios in total. The CP model has 15 decision **variables and 10 constraints for** one scenario, and 1,038 decision variables and 692 constraints for 240 scenarios. Fig.3 shows that Dupacova et al. algorithm requires approximately one third **the scenarios before the first decision is**
made correctly. It is interesting to see that the general performance of scenario reduction algorithms has deteriorated in the 4-stage case. This is mainly due to the fact that the longer the planning horizon, the better the chance of recovery from an early mistake.

![0_image_1.png](0_image_1.png)

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