Commit fb3d24bf authored by Markus Klinik's avatar Markus Klinik
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note about zero objectives

parent 2c91588b
......@@ -134,9 +134,13 @@ The weighted-product method is easier to use and can capture user preferences mo
Let $\vec{q} = \tuple{p_1, p_2, \ldots, q_1, q_2, \ldots}$ be an objective vector where the $p_i$ are more-is-better objectives and the $q_i$ are less-is-better objectives.
Let $\vec{w} = \tuple{w_1, w_2, \ldots, v_1, v_2, \ldots}$ be the weights, pre-determined by the decision maker.
The score $s$ of an objective vector is calculated using the weighted product according to the following formula.
$$s = (p_1^{w_1} p_2^{w_2} \ldots) / (q_1^{v_2} q_2^{v_2} \ldots)$$
\todo{minimize objective can't be zero}
\begin{IEEEeqnarray*}{c}
s = (p_1^{w_1} p_2^{w_2} \ldots) / (q_1^{v_2} q_2^{v_2} \ldots)
\end{IEEEeqnarray*}
As less-is-better objectives occur in the denominator, they can not be zero.
If a more-is-better objective is zero, the whole score will be zero, which might not be desirable.
Programmers of quality functions need to take both into account.
Some of the properties of the weighted-product method relevant for c2 scheduling are as follows.
\paragraph{Mixed units of measurement}
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