The Reliability and Quantitative Decision Making Techniques

The moment of decision making is risk birth time. We ever effort to step toward decreasing the risk, and in the other word, to increase the reliability in decision making by developing our decision making process. The decision making process can be divided to two main stages. The first stage includes inspection of environment and its dominant conditions, specifying the effective factors and data collecting. The second stage includes selecting an appropriate decision making method, performing the model and analyzing the obtained results. For increasing the reliability in the first stage, we are into specifying all factors which effect on the decision, by perfect inspecting the environment and its present dominant condition and also broadcasting the future conditions, if it is possible; and collect perfect data from reliable and valid resources and references. In the second stage, the reliability can be increased, by selecting the appropriate decision making method. Appling mixed decision making models is one of the best solutions for increasing the reliability in this stage, because the specifications and advantages of several techniques join together in a mixed model. In this paper, firstly an introduction of the two most important Decision Making techniques (MADM), means Analytic Hierarchy Process (AHP) and Technique Multi-Attribute for Ordering Preference by Similarity to Ideal Solution (TOPSIS) is stated, and then a mixed model based on these two techniques is suggested. A case study of automobile industry is stated, which demonstrates the results of each three techniques. Our results show, when two decision making techniques (AHP, TOPSIS) with the same data and condition, give different results which cause decision maker’s unreliability and hesitate, then the suggested mixed model (AT) presents a result which is between the results of two previous techniques with their specifications and advantages, and therefore is more reliable.

کلیدواژه ها:

Reliability ، AHP ، TOPSIS ، Mixed model ، Automobile industry