The value/utility function approaches to MODM are based on multiattribute utility theory. These methods assume that the decision maker behaves according to the value/utility maximizing decision rule (Keeney and Raiffa 1976, Steuer 1986). In addition, the existence of an individual or group value/utility function (also called a preference function) is assumed. The utility function approach deals with the case when some probability measure (uncertainty) is incorporated into a decision maker’s preferences, while the value function techniques are used in deterministic decision situations. It is important to recognize the difference between the value/utility approaches to MODM and the MADM value/utility function methods. Since for the MADM problem a finite set of alternatives is evaluated, the value/utility function decision rule selects the alternative that results in the highest value of the value/utility function. Thus, once the multiattribute value/utility fuction is obtained, the solution to the MADM problem becomes straightforward. However, the in case of the MODM problem, where a large or an infinite set of feasible alternatives must be evaluated, the problem must be solved using mathematical programming methodology.
Graphical Ontology Browser
- Click on a node to jump to the content of that node
- Pan to see the rest of the graph
- Scroll the mousewheel up and down to zoom in and out
- Rearrange the nodes in the graph by dragging a node to a different position