AN INTEGRATED INTELLIGENT SYSTEM FOR CONSTRUCTION INDUSTRY: A CASE STUDY OF RAISED FLOOR MATERIAL
This paper aims to introduce a quantitative method to builders for the most appropriate material selections based on multiple attributes and integrate decision group member opinions throughout bidding process. In this respect, a new model used together with the Analytic Hierarchy Process (AHP) and f...
Gespeichert in:
Veröffentlicht in: | Technological and economic development of economy 2018-10, Vol.24 (5), p.1866-1884 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | This paper aims to introduce a quantitative method to builders for the most appropriate material selections based on multiple attributes and integrate decision group member opinions throughout bidding process. In this respect, a new model used together with the Analytic Hierarchy Process (AHP) and fuzzy Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), multi-criteria decision methods are proposed. In a real decision process, there are many uncertainties and ambiguities. In fact decision makers cannot always provide practical guidelines and especially precise judgments due to time limitations. The intelligent model proposed demonstrates that the AHP and fuzzy MOORA approach can not only be used easily to imitate the decision duration in the material selection but also the results obtained from this work provide contractors valuable insight into the material selection problem. At the same time, the quantitative analysis method based on the appropriately raised floor materials along the bidding process enables the builders to use their restricted resources more expeditiously and enhances considerably the possibility of winning agreement, as one of the most striking points deduced from the present study. In short, the model with AHP and fuzzy MOORA approaches can assist the builders to improve resolutions for the bidding. |
---|---|
ISSN: | 2029-4913 2029-4921 |
DOI: | 10.3846/20294913.2017.1334242 |