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Unambiguous Goal Seeking Through Mathematical Modeling
Abstract
All decision-making support systems (DMSS) provide both input and output feedback for the user. This feedback helps the user find a problem solution and captures any created knowledge for future reference. Goal seeking is an important form of DMSS feedback that guides the user toward the problem solution. Often in the decision support literature there is a concentration on providing forward-oriented decision assistance. From this perspective, the decision problem is viewed from the problem forward, towards a solution and advice is given with that orientation. In the literature, this is most often seen in “what-if” analysis. Goal seeking takes an inverted view where a preferred or optimal solution is known and the advice provided identifies values for the decision problem variables so that the optimal or preferred solution is obtained. Goal seeking approaches can be useful not only in identifying a solution, but also examining and explaining the relationships between decision variables. Unlike what-if analysis, which is forward oriented, goal seeking starts with a preferred outcome and decision makers do not have to manipulate decision variables in a recursive manner to examine different decision scenarios.
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