A Study on the Development of a Cost Model Based on the Owner's Decision Making at the Early Stages of a Construction Project

• Authors: Choong-Wan Koo , TaeHoon Hong , Chang-Taek Hyun , Sang H. Park , Joon-oh Seo

Title variants

LT

Kainos modelio nustatymo tyrimas pagal savininko sprendimą ankstyvaisiais statybos projekto etapais

Abstracts

EN

Decision making at the early stages of a construction project has a significant impact on the project, and various scenarios created based on the owner's requirements should be considered for the decision making. At the early stages of a construction project, the information regarding the project is usually limited and uncertain. As such, it is difficult to plan and manage the project (especially cost planning). Thus, a cost model that could be varied according to the owner's requirements was developed. The cost model that was developed in this study is based on the case-based reasoning (CBR) methodology. The model suggests cost estimation with the most similar historical case as a basis for the estimation. In this study, the optimization process was also conducted, using genetic algorithms that reflect the changes in the number of project characteristics and in the database of the model according to the owner's decision making. Two optimization parameters were established: (1) the minimum criteria for scoring attribute similarity (MCAS); and (2) the range of attribute weights (RAW). The cost model proposed in this study can help building owners and managers estimate the project budget at the business planning stage.

LT

Sprendimų priėmimas ankstyvuoju statybos projekto etapu turi didelę įtaką projektui ir įvairiems scenarijams, remiantis savininko reikalavimais, kurių turi būti laikomasi priimant sprendimus. Ankstyvaisiais statybos projekto etapais informacijos apie projektą paprastai yra nedaug ir ji nėra patikima. Dėl to sudėtinga planuoti ir taisyti projektą (ypač išlaidų planavimą). Todėl šio tyrimo metu buvo sukurtas kainos modelis, kuris galėtų būti keičiamas atsižvelgiant į savininko poreikius. Kainos modelis, kuris buvo sukurtas šio tyrimo metu, remiasi atvejų analize, pagrįsta argumentų metodika (angl. CBR). Modelis siūlo sąmatinius skaičiavimus su panašiausiais ankstesniais atvejais, kurie yra skaičiavimo pagrindas. Šio tyrimo metu procesas buvo optimizuotas naudojant genetinius algoritmus, rodančius projektų skaičiaus kitimą tam tikro modelio duomenų bazėje pagal savininko priimamus sprendimus. Buvo nustatyti du optimizavimo parametrai: 1) minimalūs kriterijai veiksnių panašumui įvertinti (angl. MCAS); 2) veiksnių svorių vertinimo intervalas (angl. RAW). Kainos modelis, pasiūlytas šiame tyrime, gali padėti pastatų savininkams ir valdytojams įvertinti projekto biudžetą verslo planavimo etape.

Keywords

EN

Case-based reasoning; Cost planning; Optimization

• Publisher: Sciendo
• Journal: International Journal of Strategic Property Management
• Year: 2010
• Volume: 14
• Issue: 2
• Pages: 121-137

Contributors

author

Choong-Wan Koo

• HanmiParsons Co., Ltd., Seoul, Korea

author

TaeHoon Hong

• Department of Architectural Engineering, Yonsei University, Seoul, Korea

author

Chang-Taek Hyun

• Department of Architectural Engineering, University of Seoul, Seoul, Korea

author

Sang H. Park

• HanmiParsons Co., Ltd., Seoul, Korea

author

Joon-oh Seo

• HanmiParsons Co., Ltd., Seoul, Korea

References

• Dogan, S. Z., Arditi, D. and Gunaydin, H. M. (2006) Determining attribute weights in a CBR model for early cost prediction of structural systems,Journal of Construction Engineering and Management-ASCE, 132(10), pp. 1092-1098. doi:10.1061/(ASCE)0733-9364-(2006)132:10(1092)
• Hegazy, T. and Ayed, A. (1998) Neural network model for parametric cost estimation of highway projects,Journal of Construction Engineering and Management-ASCE, 124(3), pp. 210-218. doi:10.1061/(ASCE)0733-9364(1998)124:3(210)
• Kim, G., Kim, S. and Kang, K. (2004) Comparing accuracy of prediction cost estimation using case-based reasoning and neural networks,Journal of the Architectural Institute of Korea, 20(5), pp. 93-102.
• Koo, C., Hong, T., Hyun, C. and Koo, K. (2010) A CBR-based hybrid model for predicting a construction duration and cost based on project characteristics in public multi-family housing projects, Paper scheduled for publication in theCanadian Journal of Civil Engineering.
• Lowe, D. J., Emsley, M. W. and Harding, A. (2006) Predicting construction cost using multiple regression techniques,Journal of Construction Engineering and Management-ASCE, 132(7), pp. 750-758. doi:10.1061/(ASCE)0733-9364-(2006)132:7(750)
• Phaobunjong, K. (2002)Parametric cost estimating model for conceptual cost estimating of building construction projects.Ph.D thesis, University of Texas, Austin, Texas.
• Haupt, R. L. and Haupt, S. E. (2004)Practical genetic algorithms, 2ndedition, John Wiley & Sons, Inc., Hoboken, New Jersey.
• Rifat, S. (2004) Conceptual cost estimation of building projects with regression analysis and neural networks,Canadian Journal of Civil Engineering, 31(2), pp. 677-683.
• Ryu, H. (2007)Construction planning methodology using case-based reasoning(CONPLA-CBR). Ph.D thesis, Seoul National University, Seoul, Korea.
• Watson, I. (1997)Applying case-based reasoning: techniques for enterprise systems, Morgan Kaufmann Publishers, Inc., San Francisco, California.

Identifiers

DOI

10.3846/ijspm.2010.10