Bayesian Markov Chain Monte Carlo Model for Determining Optimum Tender Price in Multifamily Housing Projects

Title
Bayesian Markov Chain Monte Carlo Model for Determining Optimum Tender Price in Multifamily Housing Projects
Author(s)
김상용김광희[김광희]이동운[이동운]
Keywords
COST; CONSTRUCTION; REGRESSION
Issue Date
201405
Publisher
ASCE-AMER SOC CIVIL ENGINEERS
Citation
JOURNAL OF COMPUTING IN CIVIL ENGINEERING, v.28, no.3
Abstract
This study presents a strategy model for determining the optimum tender price that reflects appropriate profit and risk contingencies in competitive tendering according to the Bayesian Markov Chain Monte Carlo (BMCMC) model. The BMCMC approach is known to be theoretically optimal for handling tender-price problems. The BMCMC model provides a practical solution that can reflect not only objective information but also subjective experience and knowledge. The BMCMC model allows contractors to estimate the tender price more accurately by reflecting the prior distribution function on key factors. Conclusively, this model was found to improve decision-making processes for setting an optimum tender price. An applied example showed that the proposed methods are feasible. (C) 2014 American Society of Civil Engineers.
URI
http://hdl.handle.net/YU.REPOSITORY/32191http://dx.doi.org/10.1061/(ASCE)CP.1943-5487.0000297
ISSN
0887-3801
Appears in Collections:
건축학부 > 건축학부 > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE