Adapting the Multi-Objective Parametric Optimization Model for Prioritization of Urban Transportation Goals

Document Type : Scientific - Research

Author

Assistant Professor, Department of Civil Engineering, Bu Ali Sina University, Hamadan, Iran

Abstract

One of the most important steps in conducting transportation studies or implementing transportation improvement actions is to determine the importance and priority of the city's transportation goals. In general, two types of targets can be defined in transportation studies: goals and objectives. This article seeks to provide a method for the prioritization of the transportation goals, in such a way that the opinion of all people (officials, operators and experts) related to the transportation issue is taken into account in this priority. In the proposed method, after receiving the opinion of all people about the scores and priority of each goal, an integrated prioritization from the general viewpoint will be achieved through a proposed parametric model. The proposed parametric model is built upon adapting the well-known Multi-Objective Parametric Optimization model. The idea had been that given the dispersion of the scores within different people, the dominance structure should also be considered in addition to the average relative scores of the goals. The proposed method has been applied to prioritize the transportation goals of the city of Mashhad. Results show that if the dispersion of scores is not considered (and one uses the Simple Additive Weighting method, which prioritize the goals just simply based on the average relative scores), it will be accompanied by a decision error. The results of this study indicate that the first three goals obtained from both simple weighting method and the proposed method are analogous in Mashhad, but the fourth priority are different.

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References

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Quarterly Journal of Transportation Engineering
Volume 11, Issue 2 - Serial Number 43
January 2020
Pages 383-400

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History

  • Receive Date: 29 January 2018
  • Revise Date: 27 October 2018
  • Accept Date: 31 October 2018

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