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Stochastic Programming - Index of

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RECOURSE PROBLEMS 193<br />

φ<br />

φ<br />

α<br />

β<br />

α<br />

β<br />

ξ<br />

ξ<br />

Figure 19 An illustration <strong>of</strong> a situation where both α and β give good<br />

information about curvature.<br />

The parameters α and β contain information about the curvature <strong>of</strong> φ(ξ).<br />

In particular, note that if, for example, α =0thenπ B is an optimal dual<br />

solution corresponding to ξ = A. Ifπ A ≠ π B in such a case, we are simply<br />

facing dual degeneracy. In line with this argument, a small α (or β) should<br />

mean little curvature. But we may, for example, have α large and β small. So<br />

what is going on<br />

Figure 19 shows two different cases (both in one dimension), where both α<br />

and β are good indicators <strong>of</strong> how important a random variable is. Intuitively, it<br />

seems reasonable to say that the left part <strong>of</strong> the figure indicates an important<br />

random variable, and the right part an unimportant one. And, indeed, in the<br />

left part both α and β will be large, whereas in the right part both will be<br />

small.<br />

But then consider Figure 20. Intuitively, the random variable is<br />

unimportant, but, in fact, the slopes at the end points are the same as in<br />

the left part <strong>of</strong> Figure 19, and the slopes describe how the objective changes<br />

as a function <strong>of</strong> the random variable. However, in this case α is very small,<br />

whereas β is large. What is happening is that α and β pick up two properties<br />

<strong>of</strong> the recourse function. If the function is very flat (as in the right part <strong>of</strong><br />

Figure 19) then both parameters will be small. If the function is very nonlinear<br />

(as in the left part <strong>of</strong> Figure 19), both parameters will be large. But if

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