Intuitionistic Fuzzy Factorial Analysis Model for Supplier Selection of Urban Rail Transit Companies within a Random Environment
Author(s) -
Hui Sun,
Han-Lin Li,
Yuning Wang,
Yufei Yang
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/6676344
Subject(s) - urban rail transit , selection (genetic algorithm) , factorial analysis , transport engineering , computer science , public transport , rail transit , fuzzy logic , operations research , business , engineering , mathematics , artificial intelligence , statistics
Facing serious environmental and traffic problems, urban rail transit companies, with the features of large capacity and high efficiency, have become an important choice for many large cities that are prioritizing public transportation and encouraging green travel options. As the construction speed of rail transit projects accelerates, the demand for materials and devices required for construction and operation is also increasing for urban rail transit companies. Therefore, the scientific selection of suppliers to meet construction and operation demands has become a problem that must be addressed. This paper presents an intuitionistic fuzzy factorial analysis model in a random environment, where correlative phenomena among each of the indicators and a random decision-making environment are considered. The evaluation indicator system of rail suppliers is established by considering the influencing factors. The extracted common factors indicate the nature of the studied object in a most direct way. The suppliers are evaluated from the perspective of the number of intuitionistic fuzzy factors and are ranked by their scores. Finally, the Tianjin urban rail transit company is used as a case study to illustrate the validity and feasibility of the method. The results can help urban rail transit companies improve their existing supplier selection method.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom