TECHNICAL PAPERS
Apr 1, 2009

Optimal Strategy Modeling for Price-Time Biparameter Construction Bidding

Publication: Journal of Construction Engineering and Management
Volume 135, Issue 4

Abstract

In the price-time biparameter construction bidding system, each contractor submits a bid price and construction time to complete the project, which are then aggregated to a total combined bid (TCB) by the client, and the contractor with the lowest TCB is awarded the project. Since bid price can be set as construction cost plus an appropriate markup and construction cost usually depends on construction time, TCB can be expressed as a function of time. By minimizing such a TCB function, the optimal construction time can be obtained, from which the optimal construction cost and bid price and hence the optimal price-time bidding strategy can be sequentially decided. While examining the whole optimal bidding process, this paper focuses on three aspects to enhance the key ideas: discussing the properties of the general and the quadratic time-cost functions, deducing the optimal bidding formulas with quadratic time-cost relationship, and illustrating the procedures for estimating the quadratic time-cost function using a few experience data and the linear regression method. The in-depth examination of the price-time biparameter bidding model in the paper can suggest ideas and methodologies to construction bidding or contractor selection with more criteria.

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Acknowledgments

This study was partly supported by a Competitive Earmarked Research Grant from the Hong Kong Research Grant Council (Project No. CityU UNSPECIFIED1129/02E).

References

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Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 135Issue 4April 2009
Pages: 298 - 306

History

Received: Mar 6, 2007
Accepted: Nov 14, 2008
Published online: Apr 1, 2009
Published in print: Apr 2009

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Lecturer, School of Mathematics and Statistics, Univ. of South Australia, City West Campus, 70 North Terrace, Adelaide, SA 5000, Australia (corresponding author). E-mail: [email protected]
Associate Professor, Dept. of Management Sciences, City Univ. of Hong Kong, 83 Tat Chee Ave., Kowloon, Hong Kong. E-mail: [email protected]

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