Project safety evaluation by a new soft computing approach-based last aggregation hesitant fuzzy complex proportional assessment in construction industry

Document Type : Article

Authors

1 Young Researchers and Elite Club, South Tehran Branch, Islamic Azad University, Tehran, Iran

2 Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran

3 Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.

4 Laboratoire de Conception, Fabrication Commande, Arts et Métier Paris Tech, Centre de Metz, Metz, France

Abstract

In recent years, the implementation of safety management has been increased in construction projects by institutions, and many companies have recognized environmental and social effects of injuries at project work systems. In this regard, a novel decision model is presented based on a new version of complex proportional assessment method with last aggregation under a hesitant fuzzy environment. The decision makers (DMs) assign their opinions by hesitant linguistic variables that are converted to the hesitant fuzzy elements. Also, the DMs’ judgments are aggregated in last step of decision making to decrease information loss. Since weights of the DMs or professional safety experts and evaluation criteria are not equal in practice, a new version of hesitant fuzzy compromise solution method is proposed to compute these weights. In addition, the criteria weights are determined based on proposed hesitant fuzzy entropy method. A real case study in developing countries about the safety of construction projects is considered to indicate the suitability and applicability of the proposed new hesitant fuzzy decision model with last aggregation approach. In addition, an illustrative example is prepared to show that the proposed approach is suitable and reliable in larger size safety problems

Keywords

Main Subjects

References

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Scientia Iranica
Volume 27, Issue 2
Transactions on Industrial Engineering (E)
March and April 2020
Pages 983-1000

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History

  • Receive Date: 20 December 2015
  • Revise Date: 25 November 2016
  • Accept Date: 20 May 2017

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