Analytical Hierarchy Process

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Analytical Hierarchy Process

Because people choose these three elements: importance, preference and likelihood to evaluate all the possible alternatives to a decision which sometimes is not consistent with every decision situation, the concept of Analytical Hierarchy Process (AHP) was developed by Dr. Thomas Saaty. Dr. Saaty described the AHP as a decision making approach based on the "innate human ability to make sound judgments about small problems"

AHP transforms complex decision problems into simple decisions for both individuals and groups that employees the use of it to make decision. It is accommodative of intuition, compromise, and consensus structure without narrow-mindedness. The main purpose of this paper is to discuss what the AHP is and some other aspects of it.

What is AHP?

Saaty suggested AHP as a process that requires structuring the decision problem to demonstrate key elements and relationships that elicits judgments reflecting feelings or emotions, and whose judgments can be represented by meaningful numbers having ratio properties. In the AHP approach, complex decisions are organized and assessed against all possible alternatives using a hierarchy of multifaceted objectives allowing for a better, easier, and more efficient identification of selection criteria.

How AHP works

AHP is used to first decompose the decision problem into a hierarchy of easily comprehended sub-problems, each of which can be analyzed independently. The elements of the hierarchy can relate to any aspect of the decision problem tangible or intangible, estimated or carefully measured, well or poorly understood.

Once that hierarchy is established, the decision maker systematically examines the various elements, comparing them to each other in pairs. In making the comparisons, the decision maker can use his/her judgments about the elements’ relative meaning and importance, or they can use well refined data about the elements.

AHP converts the judgments to numerical values that are processed, evaluated and compared over the entire range of the decision problem. A numerical weight or priority vector is derived for each element of the hierarchy, allowing diverse and often incommensurable elements to be compared to one another in a rational and consistent way. This capability distinguishes AHP from other decision making techniques.

At the end of the process, numerical priorities are derived for each of the decision alternatives. It is then a simple matter to pick the best alternative, or to rank them in order of relative preference.
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