A Mean-HSV model for uncertain subcontractor selection

Author

Xiaoxia Huang ; Xiaoyan Zhang

Author_Institution

Dongling Sch. of Econ. & Manage., Univ. of Sci. & Technol. Beijing, Beijing, China

fYear

2014

fDate

25-27 June 2014

Firstpage

1

Lastpage

5

Abstract

Subcontractor selection plays a key role for the main contractor of a complex construction project. In this paper, we identify the higher partial semi-variance (HSV) of processing times to express the risk of tardiness, and propose a Mean-HSV model to provide a formal description for the subcontractor selection problem. The objective is to select the optimal combination of subcontractors to minimize the total cost of the project within due date. The uncertainty theory is used to deal with parameters with human subjective estimation. Finally, the 99 method was used to solve the model.

Keywords

construction industry; cost reduction; investment; parameter estimation; complex construction project; higher partial semivariance identification; human subjective estimation; mean-HSV model; optimal subcontractor portfolio; risk-of-tardiness; total cost minimization; uncertain subcontractor selection problem; Computational modeling; Estimation; Indexes; Mathematical model; Portfolios; Programming; Uncertainty; higher partial semi-variance; subcontractor selection; uncertainty theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Service Systems and Service Management (ICSSSM), 2014 11th International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4799-3133-0

Type

conf

DOI

10.1109/ICSSSM.2014.6874034

Filename

6874034