A balanced risk treatment for construction projects

Georgy, M, Zabel, N and Ibrahim, M 2013, 'A balanced risk treatment for construction projects', in Siamak Yazdani and Amarjit Singh (ed.) Proceedings of New Developments in Structural Engineering and Construction, Manoa, Honolulu, 18-23 June 2013, pp. 1653-1658.


Document type: Conference Paper
Collection: Conference Papers

Title A balanced risk treatment for construction projects
Author(s) Georgy, M
Zabel, N
Ibrahim, M
Year 2013
Conference name ISEC-7
Conference location Manoa, Honolulu
Conference dates 18-23 June 2013
Proceedings title Proceedings of New Developments in Structural Engineering and Construction
Editor(s) Siamak Yazdani and Amarjit Singh
Publisher Research Publishing Services
Place of publication Singapore
Start page 1653
End page 1658
Total pages 6
Abstract Risk management is an integral part of a successful project planning and control mechanism. Standards, e.g., AS/NZS ISO 31000:2009, establish frameworks on how to perform comprehensive risk management process. However, there remain gaps in enacting such standards in reality, one of which is balancing risk treatment with the associated costs to risk-bearing project stakeholders. Although many studies were carried out to identify the range of factors representing project risk events and the recommended responses, very little has addressed the means of making such decisions. In this context, the guided search capabilities of evolutionary algorithms can play a role. After discussing and modeling the costs and benefits of alternative risk treatment strategies, the paper introduces ant colony as a capable algorithm for the balanced selection of such strategies. The research is being applied in the pipeline construction sector and made use of professional knowledge and project records from a mega construction company in the Middle East.
Subjects Building Construction Management and Project Planning
Keyword(s) Risk management
Risk treatment
Response plan
Mitigation
Optimization
Decision-making
Evolutionary algorithms
Ant colony.
DOI - identifier 10.3850/978-981-07-5354-2_RADM-13-369
Copyright notice © 2013 Research Publishing Services. All rights reserved
ISBN 9789810753542
Versions
Version Filter Type
Altmetric details:
Access Statistics: 516 Abstract Views  -  Detailed Statistics
Created: Tue, 06 May 2014, 13:05:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us