Constraint-based clustering and its applications in construction management

Authors:
Ying-Mei Cheng;Sou-Sen Leu
Affiliations:
Department of Civil Engineering, China University of Technology, 56 Hsing-Lung Road, Section 3, Taipei 116, Taiwan, ROC;Department of Construction Engineering, National Taiwan University of Science and Technology, 43 Keelung Road, Section 4, Taipei 10672, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

Both mixed data types and cluster constraints are frequently encountered in the classification problems of construction management. For example, in a bridge let project, engineers generally group the bridges into several subgroups based on their proximities, structure type, material, etc. Moreover, constraints may be set for each cluster to ensure the project's overall effectiveness. In this study, an effective clustering algorithm - the constrained k-prototypes (CKP) algorithm - is proposed to resolve the abovementioned problems. Several tests and experimental results have shown that CKP cannot only handle mixed data types but also satisfy user-specified constraints. In order to demonstrate the applicability of CKP, it is also applied to real-world problems in construction management.