Optimizing Value and Risk based on Client Expectation in Construction Industry using Intelligent Algorithm : A Case-Study in New Zealand

Authors

  • Wei Zhang  College of Civil Engineering and Architecture, Zhejiang University of Technology, Hangzhou, Zhejiang, China

Keywords:

Value Management, Client Expectation, Intelligent Algorithm

Abstract

New processes and materials pose benefits to architects, designers, and builder and home owners as such change mean the cost of building was lower and in some cases home building projects were able to be completed faster. However as with new processes and materials emerge, new training is required to fully utilize them allowing construction projects to gain added value. The goal of this paper is to illustrate how value management and risk management can be applied to manage the expectation of clients in construction projects. To achieve our goal, first it is shown that with the new ability of clients being able to access information regarding to new materials and processes, they can incorporate more than before in specifying particular materials and processes in the design and construction of the building increases. Then a novel model is provided using Intelligent Algorithm to maximize value and minimize the risk based on client expectation.

References

  1. Atkin, B., Borgbrant, J., & Josephson, P.-E. (2003). Introduction, in Construction Process Improvement. Oxford, UK.: Blackwell Science Ltd.
  2. Chu, Z.-Q., Sasanipour, J., Saeedi, M., Baghban, A., & Mansoori, H. (2017). Modeling of wax deposition produced in the pipelines using PSO-ANFIS approach. Petroleum Science and Technology, 1974-1981.
  3. Havard, T. (2002). Contemporary property development. London: RIBA Enterprises.
  4. Hessami, A. R., Sun, D., Nejat, A., Odreman, G. J., Zhou, X., & Saeedi, M. (2017). Enhanced Cost Estimating and Project Development Procedures for MPOs. Kingsville, Texas: Texas A&M University Kingsville (TAMUK). Retrieved from https://library.ctr.utexas.edu/hostedpdfs/tamuk/0-6929-s.pdf
  5. Hessami, A. R., Sun, D., Odreman, G. J., Zhou, X., Nejat, A., & Saeedi, M. (2017). Project Scoping Guidebook for Metropolitan Planning Organization Transportation Projects. Kingsville, Texas: Texas A&M University Kingsville (TAMUK).
  6. Kenley, R. (2003). Financing construction: Cash flows and cash farming. London: SPON Press.
  7. Knipe, A., Van der Waldt, G., Van Niekerk, D., Burger, D., & Nell, K. (2002). Project management for success. Heinemann.
  8. Mirmohammadsadeghi, A., & Aghdami Thani, M. R. (2005). Studying obstacles in utilization of value engineering in construction industry of Iran. The 2nd National VE Conference. Tehran, Iran.
  9. Omigbodun, A. (2001). Value engineering and optimal building projects. ASCE Journal of Architectural Engineering, 7(2), 40-43.
  10. Ramroth, W. (2006). Project Management for Design Professionals. Kaplan Business.
  11. Saeedi, M. (2017). Presenting a Novel Integrated Closed-loop Supply Chain Model by Considering Social Responsibility. Asian Journal of Applied Science and Technology, 1(8), 125-134.
  12. Torabi, A., Kiaian Mousavy, S., Dashti, V., Saeedi, M., & Yousefi, N. (2018). A New Prediction Model Based on Cascade NN for Wind Power Prediction. Computational Economics.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2018-06-30

Issue

Volume 4, Issue 8, May-June-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Wei Zhang, " Optimizing Value and Risk based on Client Expectation in Construction Industry using Intelligent Algorithm : A Case-Study in New Zealand, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 8, pp.395-407, May-June-2018.