System Engineering and Productivity

System Engineering and Productivity

Applying the Cross-Sectional Efficiency Method to Rank Efficient Units in Adjusting Particle Aggregation Optimization Algorithm Parameters

Document Type : Research Paper

Authors
1 Corresponding author: Professor, Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
2 M.Sc., Department of Industrial Engineering, Faculty of Industrial Engineering, University of Eyvanekey, Eyvanekey, Iran
Abstract
Since the DEA method measures relative efficiency and in cases where more than one efficient unit is obtained, it is not able to provide the best efficient unit. For this reason, ranking decision-making units is considered one of the important issues in DEA. One of the solutions to determine the best efficient unit is to use the cross-efficiency method to rank the work units, which is actually developed from the DEA method. This paper seeks to investigate the cross-efficiency of the efficient units provided by the DEA method and ultimately, to provide the best efficient unit from the parameter combinations of the particle aggregation optimization algorithm in solving different sizes of the open vehicle routing problem. In this study, we rank efficient units using the cross-efficiency method using previously simulated data that has provided several efficient units in evaluating the particle swarm optimization algorithm for solving each of the different sizes of the open vehicle routing problem. The results show that the cross-efficiency method is an effective tool for ranking the performance of decision-making units.
Keywords

Copyright ©, Mahdi Bashiri, Samira Rabiei

 

License

This article is released under the Creative Commons Attribution (CC BY 4.0) license. Anyone is free to copy, share, translate, and adapt this article for any purpose, whether commercial or non-commercial, as long as proper citation is given to the authors and original publication.

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Volume 1, Issue 1 - Serial Number 1
Serial No. 1, Winter Quarterly
Winter 2022
Pages 47-56

  • Receive Date 03 November 1400
  • Revise Date 13 November 1400
  • Accept Date 15 November 1400
  • First Publish Date 12 April 2021
  • Publish Date 19 May 2025