A Novel Contractor Selection Technique Using the Extended PROMETHEE II Method
Author(s) -
KueiHu Chang
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 - 10.1155/2021/3664709
Subject(s) - correctness , selection (genetic algorithm) , data envelopment analysis , quality (philosophy) , process (computing) , computer science , set (abstract data type) , product (mathematics) , order (exchange) , operations research , industrial engineering , data mining , mathematical optimization , engineering , algorithm , mathematics , artificial intelligence , business , philosophy , geometry , epistemology , finance , programming language , operating system
Selecting suitable contractors directly influences product quality, corporate profits, and even sustainable development. The selection problem of contractors is, therefore, a critical issue for the sustainable development of an enterprise. However, traditional contractor selection techniques are unable to handle information regarding the relative importance of criteria or handle nonexistent or missing data in the assessment process of contractor selection. In order to effectively address this problem, this study proposes a new contractor selection technique that integrates the concept of soft set and the PROMETHEE II method to select suitable contractors. Three numerical examples are applied to prove the correctness and effectiveness of the proposed technique. This study also compares the simulation results achieved using the proposed method with those achieved using the traditional weighted arithmetic averaging method and the data envelopment analysis (DEA) technique. The simulation results show that the proposed method is a more general contractor selection technique for handling incomplete information than the traditional weighted arithmetic averaging method and the DEA method.
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