If all pairwise comparisons matrix was collected, we can produce the final priority weights of candidate selection. Thus, if we want to create a matrix of pairwise comparisons with a number of n items, then we only need to make a comparison of a number n ( n -1 ) / 2. In addition, the diagonal values in paired comparison matrix is one (because each item is compared with itself ). In making matrix pairs, we only need to specify an upper triangular matrix only because of a lower triangular matrix is simply the value of upper triangular reprisokal. For example in the previous hierarchy, we must make a paired comparison matrix for sub - criteria of carrying capacity and sub - criteria of availability of spare parts to the criteria of the specification, the matrix of pairwise comparisons between sub - criteria purchase costs, maintenance costs and the cost of mileage perton against criteria of cost, and so on. Matrix of pairwise comparisons should be made of each level that have the same hierarchical superiors. For example, pairwise comparisons between criteria 1 and 3 is 1 / 5, meaning that three criteria strongly more important than criterion 1. Meanwhile, if his interests turned upside down, then we can use numbers reprisokal of the values above. These values describe the relationship between interest in odd values mentioned above. In addition to the above values , the values of which can also be used, namely, 2, 4, 6, and 8. These values are recommended to create a matrix of pairwise comparisons are as follows : 1: equally important ( equal )ħ: The more important is very strong ( very strong)ĩ: more important in the extreme (extreme ) Vehicle A, B, and C are compared in pairs ( and will be formed matrix ) in terms of sub - criteria such as maintenance expenses. For example, the specification criteria and cost criteria will be compared in terms of choosing how important transportation fleet. A criterion will be compared with other criteria in terms of how important to the achievement of goals on it. The basic concept is the use of the AHP pairwise comparison matrix ( matrix of pairwise comparisons ) to generate the relative weights between criteria and alternatives. While the lowest level shows the candidates will be considered for selection. Two levels below the level of criteria and sub -criteria. In the above model, it appears there are several levels / lines that form a hierarchy. This problem can be modeled as a hierarchical model of the AHP below. For example, suppose a manager is faced with the problem to choose the most suitable logistics fleet. Where a decision problem to be solved by the method of AHP, the problem needs to be modeled as three common hierarchy, namely the objectives, criteria ( including sub -criteria below ), and alternatives. Candidate selection is specific and limited in number.Assessment can be done by one or several decision makers are well.Each criterion can have sub -sub criteria that can be constructed as a hierarchy.Involve qualitative criteria that are difficult dikuantitatifkan exactly.Specifically, the AHP is used to permasalahaan selection of suitable candidates or sequencing of priorities which has properties as follows : One tool ( a tool ), suitable for the selection of candidates or sequencing priority is the Analytic Hierarchy Process ( AHP ) developed by Thomas L. Problems of decision making can be complex because of the involvement of multiple objectives and criteria. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.įor technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Matthew Walls (email available below). If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. You can help adding them by using this form. We have no bibliographic references for this item. It also allows you to accept potential citations to this item that we are uncertain about. This allows to link your profile to this item. If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. See general information about how to correct material in RePEc.įor technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:36:y:1990:i:3:p:249-258. You can help correct errors and omissions. All material on this site has been provided by the respective publishers and authors.
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