A three-way decision-making technique based on Pythagorean double hierarchy linguistic term sets for selecting logistic service provider and sustainable transportation investments

• DOI: 10.3934/math.2023951
• Publication Date: 2023-06-02T11:13:43Z
• Authors: Abbas Qadir; Shadi N. Alghaffari; Shougi S. Abosuliman; Saleem Abdullah
• Keywords: Rough Sets Theory and Applications; Artificial intelligence; Decision Analysis; Semantic Trajectories; Economics; Environmental Decision Making; Trajectory Data Mining and Analysis; Social Sciences; Geometry; Three-Way Decisions; Group Decision Making; Multi-Criteria Decision Making; Management Science and Operations Research; Operator (biology); Operations research; Biochemistry; Quantum mechanics; Gene; Term (time); Decision Sciences; Systems engineering; FOS: Economics and business; Task (project management); Engineering; Hierarchy; Service (business); Market economy; QA1-939; FOS: Mathematics; three way decision making; Business; pythagorean fuzzy double linguistic term set; pythagorean fuzzy double linguistic aggregation operators; Pythagorean theorem; Marketing; Analytic hierarchy process; Physics; linguistic variable; Computer science; Service provider; Chemistry; Computational Theory and Mathematics; Computer Science; Physical Sciences; Signal Processing; Repressor; Transcription factor; Mathematics

<abstract><p>Finding the best transportation project and logistic service provider is one for the most important aspects of the development of a country. This task becomes more complicated from time to time as different criteria are involved. Hence, this paper proposes an approach to the linguistic three-way decision-making (TWDs) problem for selecting sustainable transportation investments and logistic service providers with unknown criteria and expert weight information. To this end, we first propose a new tool, the Pythagorean double hierarchy linguistic term sets (PyDHLTSs), which is a combination of first hierarchy linguistic term sets and second hierarchy linguistic term sets which can describe uncertainty and fuzziness more flexibly in decision-making (DM) problems. In addition, we propose some aggregation operators and basic operational laws for PyDHLTSs. A new decision-making technique for PyDHLTSs based on decision-theoretic rough sets (DTRSs) is proposed in the three-way decisions. Next, the conditional probability is computed using grey relational analysis in a PyDHLTSs environment, which improves decision-making. The loss function is computed by using the proposed aggregation operator, and the decision's results are determined by the minimum-loss principle. Finally, a real-world case study of a transportation project and logistic service provider is considered to demonstrate the efficiency of the proposed methods.</p></abstract>