Search results for "Weighting coefficient"

showing 2 items of 2 documents

A Priori Methods

1998

In the case of a priori methods, the decision maker must specify her or his preferences, hopes and opinions before the solution process. The difficulty is that the decision maker does not necessarily know beforehand what it is possible to attain in the problem and how realistic her or his expectations are. The working order in these methods is: 1) decision maker, 2) analyst.

Mathematical optimizationMultiobjective optimization problemWeighting coefficientComputer scienceOrder (business)Goal programmingA priori and a posterioriAspiration levelDecision maker
researchProduct

A Posteriori Methods

1998

A posteriori methods could also be called methods for generating Pareto optimal solutions. After the Pareto optimal set (or a part of it) has been generated, it is presented to the decision maker, who selects the most preferred among the alternatives. The inconveniences here are that the generation process is usually computationally expensive and sometimes in part, at least, difficult. On the other hand, it is hard for the decision maker to select from a large set of alternatives. One more important question is how to present or display the alternatives to the decision maker in an effective way. The working order in these methods is: 1) analyst, 2) decision maker.

Set (abstract data type)Generation processMultiobjective optimization problemPareto optimalMathematical optimizationWeighting coefficientOrder (exchange)Computer scienceA priori and a posterioriDecision maker
researchProduct