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measured, and the appropriate level of effectiveness is
known. Again, practical application requires that each of
the alternatives be put on an equal effectiveness basis.
This rule is dual to the one above in the following sense:
For a given level of cost, the same alternative would be
chosen by both rules; similarly, for a given level of
effectiveness, the same alternative would be chosen by
both rules.
When it is not practical to equalize the cost or
the effectiveness of competing alternatives, and cost
caps or effectiveness floors do not rule out all
alternatives save one, then it is necessary to form,
either explicitly or implicitly, a costeffectiveness
objective function like the one shown in Figure 4
(Section 2.5). The costeffectiveness objective function
provides a single measure of worth for all combinations
of cost and effectiveness. When this selection rule is
applied, the alternative with the highest value of the
costeffectiveness objective function is chosen.
Another group of selection rules is needed when
cost and/or effectiveness cannot be represented as
scalar quantities. To choose the best alternative, a
multiobjective
selection
rule
is
needed.
A
multiobjective rule seeks to select the alternative that,
in some sense, represents the best balance among
competing objectives. To accomplish this, each
alternative is measured (by some quantitative NASA Systems Engineering Handbook
Systems Analysis and Modeling Issues
method) in terms of how well it achieves each objective.
For example, the objectives might be national prestige,
upgrade or expansion potential, science data return, low
cost, and potential for international partnerships. Each
alternative's "scores" against the objectives are then
combined in a value function to yield an overall figure of
merit for the alternative. The way the scores are
combined should reflect the decision maker's preference
structure. The alternative that maximizes the value
function (i.e., with the highest figure of merit) is then
selected. In essence, this selection rule recasts a
multiobjective decisi...
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 Spring '13
 Mr.Kau
 Systems Engineering, The American

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