Hierarchical Decision-making using a New Mathematical Model based on the Best-worst Method

Authors

  • Mohammad Hashemi Tabatabaei Department of Industrial Management Faculty of Management and Accounting, Allameh Tabataba’i University, 14348-63111 Tehran, Iran
  • Maghsoud Amiri Department of Industrial Management Faculty of Management and Accounting, Allameh Tabataba’i University, 14348-63111 Tehran, Iran
  • Mohammad Ghahremanloo Department of Management Faculty of Industrial Engineering and Management, Shahrood University of Technology, 36199-95161 Shahrood, Iran , m.ghahremanloo@shahroodut.ac.ir
  • Mehdi Keshavarz-Ghorabaee Department of Management Faculty of Humanities (Azadshahr Branch), Gonbad Kavous University, 49717-99151 Gonbad Kavous, Iran m.keshavarz@gonbad.ac.ir,
  • Edmundas Kazimieras Zavadskas Vilnius Gediminas University
  • Jurgita Antucheviciene Department of Construction Management and Real Estate Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania

Keywords:

decision model, MCDM, best-worst method, hierarchical decisionmaking, pairwise comparison

Abstract

Decision-making processes in different organizations often have a hierarchical and multilevel structure with various criteria and sub-criteria. The application of hierarchical decision-making has been increased in recent years in many different areas. Researchers have used different hierarchical decision-making methods through mathematical modeling. The best-worst method (BWM) is a multi-criteria evaluation methodology based on pairwise comparisons. In this paper, we introduce a new hierarchical BWM (HBWM) which consists of seven steps. In this new approach, the weights of the criteria and sub-criteria are obtained by using a novel integrated mathematical model. To analyze the proposed model, two numerical examples are provided. To show the performance of the introduced approach, a comparison is also made between the results of the HBWM and BWM methodologies. The analysis demonstrates that HBWM can effectively determine the weights of criteria and sub-criteria through an integrated model.

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Published

2020-02-02

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