Designing efficient material handling systems: A two-stage approach based on DEA cross-efficiency

Amar Oukil*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

The process of selecting material handling (MH) models as well as evaluating related MH systems is a milestone for the design of manufacturing and logistics facilities. In order to support managers towards this process, we propose a new methodology, based on data envelopment analysis (DEA), and deploying over two stages. In the first stage, the best MH models are selected on the ground of the MH manufacturer's technical specifications and market prices. In the second stage, alternative MH systems are produced through combinations of best MH models picked in preset numbers, from different category pools, according to a set of criteria. For both stages, we develop a DEA cross-evaluation framework that exploits the voting system embedded under the cross-efficiency matrix and integrates the manager's subjective judgment as an essential component of the decision making process. The proposed procedure is illustrated using a sample of MH equipment collected from catalogues of MH manufacturers and vendors.

Original languageEnglish
Title of host publicationProceedings - 2020 5th International Conference on Logistics Operations Management, GOL 2020
EditorsYoussef Benadada, Fatima-Zahra Mhada
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728164250
DOIs
Publication statusPublished - Oct 28 2020
Event5th International Conference on Logistics Operations Management, GOL 2020 - Virtual, Rabat, Morocco
Duration: Oct 28 2020Oct 30 2020

Publication series

NameProceedings - 2020 5th International Conference on Logistics Operations Management, GOL 2020

Conference

Conference5th International Conference on Logistics Operations Management, GOL 2020
Country/TerritoryMorocco
CityVirtual, Rabat
Period10/28/2010/30/20

Keywords

  • Cross-efficiency
  • Data envelopment analysis
  • Design evaluation
  • Material handling equipment

ASJC Scopus subject areas

  • Strategy and Management
  • Artificial Intelligence
  • Computer Networks and Communications
  • Management Science and Operations Research
  • Modelling and Simulation

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