Determination of Optimal Vehicle Selection of Logistics Companies with AHP-ARAS Hybrid Method

Hakan Murat Aslan

Alphanumeric Journal, 2017, vol. 5, issue 2, 271-282

Abstract: One of the serious problems in the logistics sector is the failure to make mistakes that cause economic consequences in the bulk purchases of trucks which are the important elements of road transport. Logistics Businesses can make in place and right decisions by using multi-criteria decision-making methods in the face of similar decision problems. In this study; Logistics, transportation, criteria for purchasing of vehicles and information about the decision analysis methods ARAS (Additive Ratio Assesment) and AHP (Analytic hierarchy Proses) were given. In particular, the applicability and results of the scientific methods are emphasized in the decision of procurement of bulk vehicles by logistics companies. The study's logistic decision problem was analyzed using ARAS and AHP methods together. It can be used in different decision problems of other logistics companies by making a partial change in the alternatives and criteria of the created solution model. The model for the study was applied to the decision problem of purchasing bulk vehicles in a Georgia-based logistics company. Managers of the business as decision makers have been accepted. Criteria and alternatives have been identified by the managers, independently of each other by scoring these elements. As a result of analysis of related decision problem by AHP-ARAS hybrid method; A1 (Volvo) has become the preferred brand for bulk vehicle purchasing by the company in the first place. In addition, the analysis results are shared with the business.

Keywords: AHP; AHP-ARAS Hybrid Method; ARAS; Bulk Vehicle Purchase; Logistics Companies; Multi Criteria Decision Making (search for similar items in EconPapers)
JEL-codes: C44 (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:anm:alpnmr:v:5:y:2017:i:2:p:271-282

DOI: 10.17093/alphanumeric.339476

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