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Risk-based Framework for Management of Construction Projects

Title:

Risk-based Framework for Management of Construction Projects

Mohammadjavad, Arabpour Roghabadi ORCID: https://orcid.org/0000-0002-3924-8375 (2020) Risk-based Framework for Management of Construction Projects. PhD thesis, Concordia University.

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Abstract

Well-developed risk management tools provide critical support for successful delivery of construction projects. Considerable research has been conducted towards integration of risk management in front-end planning and in execution phases of this class of projects. The accuracy of these tools relies heavily on their respective assumptions and on the data used in their application. Consideration of risk in these tools utilizes two types of data: actual past records and estimated future data related to completion of projects under consideration. The literature reveals that most published work in this area utilized these data either in bidding phase or in one of individual project execution phases to minimize the negative impact of risk on project cost and duration at completion. However, there is a lack of a comprehensive framework that employs both types of data in different phases of construction projects. This prevents construction practitioners from implementing an efficient risk management program. In this research, a new risk-based framework is developed, addressing limitations of existing models for different management functions over project lifecycle. The developed framework employs past performance data of construction organizations and projects in the bidding phase for risk maturity evaluation, contingency estimation, markup estimation, planning and scheduling, and progress reporting. The framework has five developed models. The first introduces a decision support model for risk maturity evaluation of construction organizations to identify their strengths and weaknesses in risk management processes, employing the Analytic Network Process (ANP) and fuzzy set theory. It enables construction organizations to assess and continuously improve their risk management capabilities. The second model introduces a new cost contingency estimation model considering correlations among project cost items, subjectively and objectively. It is also capable of modeling project cost contingency with and without the use of Monte Carlo simulation, which is deemed particularly useful when using subjective correlations. The third model introduces new pattern recognition techniques for estimating project markup. It utilizes Multiple Regression (MR), Artificial Neural Network (ANN) and Adaptive Nero-Fuzzy Inference System (ANFIS) techniques for that purpose, considering five factors: need for work, job uncertainty, job complexity, market condition, and owner capability. The fourth model introduces a newly developed multi-objective optimization model for scheduling of repetitive projects under uncertainty. The model considers the estimated cost contingency and the project markup in the total project cost and conducts, simultaneously, trade-offs between project duration, project cost, crew work interruptions, and interruption costs. It safeguards against assignment of unnecessary costly resources and provides a reliable project baseline. The fifth model presents a newly developed risk-based earned duration management model (RBEDM) that utilizes the generated project baseline in forecasting project duration at completion, considering critical activities only and their associated risk factors. It introduces a new risk adjustment factor (RAFcr) that quantifies the impact of future uncertainties associated with critical activities in estimating project duration at completion. This unique aspect of the developed model addresses the main drawback of earned duration management (EDM) its reliance on past performance data only. It also assists project managers in estimating more accurate and realistic required time to project completion.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (PhD)
Authors:Mohammadjavad, Arabpour Roghabadi
Institution:Concordia University
Degree Name:Ph. D.
Program:Building Engineering
Date:13 December 2020
Thesis Supervisor(s):Moselhi, Osama
Keywords:Risk management; Project management, Construction projects; Construction organizations, Planning and scheduling, Risk maturity, Contingency estimation, Markup estimation, Earned value management, Earned duration management.
ID Code:987713
Deposited By: MohammadJavad Arabpour Roghabadi
Deposited On:29 Jun 2021 20:45
Last Modified:29 Jun 2021 20:45
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References:

AACE International., (2013), “Required Skills and Knowledge of Decision and Risk Management.” Association for the Advancement of Cost Engineering: Morgantown, WV, USA.
Acebes, F., Pajares, J., Galán, J.M. and López-Paredes, A., (2014). “A new approach for project control under uncertainty. Going back to the basics.” International Journal of Project Management, 32(3), 423-434.
Acebes, F., Pereda, M., Poza, D., Pajares, J. and Galán, J.M., (2015). “Stochastic earned value analysis using Monte Carlo simulation and statistical learning techniques.” International Journal of Project Management, 33(7), 1597-1609.
Adeli, H., and Karim, A. (1997). “Scheduling/cost optimization and neural dynamics model for construction” Journal of Construction Engineering and Management, 123 (4), 450-458.
Agrama, F. A. (2014). “Multi-objective genetic optimization for scheduling a multi-storey building”. Automation in Construction, 44, 119-128.
Ahmad, I. and Minkarah, I., (1988). “An expert system for selecting bid markups.” In Computing in Civil Engineering: Microcomputers to Supercomputers, 229-238.
Alashwal, A.M., Abdul-Rahman, H., Asef, A., (2017). “Influence of organizational learning and firm size on risk management maturity.” Journal of Construction Engineering and Management, 33, 04017034.
Altuwaim, A., and El-Rayes, K. (2018a). “Minimizing duration and crew work interruptions of repetitive construction projects” Automation in Construction, 88, 59-72.
Altuwaim, A., and El-Rayes, K. (2018b). “Optimizing the Scheduling of Repetitive Construction to Minimize Interruption Cost” Journal of Construction Engineering and Management, Vol. 144 No. 7, p. 04018051.
Amaya, A.J.R., Lengerke, O., Cosenza, C.A.N., Dutra, M.S., Tavera, M.J., (2009). “Comparison of defuzzification methods: Automatic control of temperature and flow in heat exchanger. “Automation Control Theory and Practice., A.D. Rodic, In Tech, London, UK, Volume 6, 77–88.
Ammar, M. A. (2013). “LOB and CPM integrated method for scheduling repetitive projects” Journal of Construction Engineering and Management, 139 (1), 44-50.
Andrade, P.A., Martens, A. and Vanhoucke, M., (2019). “Using real project schedule data to compare earned schedule and earned duration management project time forecasting capabilities.” Automation in Construction, 99, 68-78.
Arditi, D., and Albulak, M. Z. (1979). “Comparison of network analysis with line-of-balance in a linear repetitive construction project.” Sixth internet Conference, Garmisch-Partenkirchen, W. Germany, 12-25.
Ashley, D. B. (1980). “Simulation of repetitive-unit construction” J. Constr. Div, 106(2), 185-194.
Association for the Advancement of Cost Engineering (AACE) International, (2010), “Cost Engineering Terminology Practice No. IOS-90.” TCM Framework: General Reference.
Attalla, M. and Hegazy, T., (2003). “Predicting cost deviation in reconstruction projects: Artificial neural networks versus regression.” Journal of construction engineering and management, 129(4), 405-411.
Awad M, Khanna R., (2015) “Multiobjective optimization.” Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers. ”, Springer, Berkeley, CA, 185–208.
Azeez D, Ali MA, Gan KB, Saiboon I., (2013) “Comparison of adaptive neuro-fuzzy inference system and artificial neutral networks model to categorize patients in the emergency department.” SpringerPlus. 2(1):416.
Babar, S., Thaheem, M.J. and Ayub, B., (2017). “Estimated cost at completion: Integrating risk into earned value management.” Journal of Construction Engineering and Management, 143(3), p.04016104.
Baccarini, D. (2004). “Accuracy in estimating project cost construction contingency: A statistical analysis.” Proceedings of Construction and Building Research Conference of RICS, RICS, London, U.K.
Baccarini, D. (2005). “Estimating project cost contingency: Beyond the 10% syndrome.” Proceedings of Australian Institute of Project Management Conference, Australian Institute of Project Management, Sydney, Australia
Bakhshi, P., and Touran, A., (2014). “An Overview of Budget Contingency Calculation Methods in Construction Industry.” Procedia Engineering, 85, 52-60.
Bakry, I., Moselhi, O., and Zayed, T. (2014). “Optimized acceleration of repetitive construction projects” Automation in construction, 39, 145-151.
Bakry, I., Moselhi, O., and Zayed, T. (2016). “Optimized scheduling and buffering of repetitive construction projects under uncertainty” Engineering, Construction and Architectural Management, 23 (6),782-800.
Ballesteros-Pérez, P., Sanz-Ablanedo, E., Mora-Melià, D., González-Cruz, M.C., Fuentes-Bargues, J.L. and Pellicer, E., (2019). “Earned Schedule min-max: Two new EVM metrics for monitoring and controlling projects.” Automation in Construction, 103, 279-290.
Beckers, F., Chiara, N., Flesch, A., Maly, J., Silva, E. and Stegemann, U., (2013). “A risk-management approach to a successful infrastructure project.” Mckinsey Work. Pap. Risk, (52), p.18.
Birrell, G. S. (1980). “Construction planning—beyond the critical path” Journal of the Construction Division,106 (3), 389-407.
Carr, R.I., 1987. “Optimum markup by direct solution.” Journal of Construction Engineering and Management, 113(1), 138-150.
Chao L-C, Skibniewski MJ., (1994). “Estimating construction productivity: Neural-network-based approach.” Journal of Computing in Civil Engineering, 8(2):234-51.
Chen, D., & Hartman, F. T. (2000). “A neural network approach to risk assessment and contingency allocation.” AACE International Transactions, RI7A.
Chou, J. -S., Pham, A. D., Wang, H., (2013). “Bidding Strategy to Support Decision-Making by Integrating Fuzzy AHP and Regression-Based Simulation.” Automation in Construction, 35, 517-527.
Cox, E. (1998). “The Fuzzy Systems Handbook.” AP Professional: Boston, MA, USA.
Damci, A., Arditi, D., and Polat, G. (2013). “Multiresource leveling in line-of-balance scheduling” Journal of Construction Engineering and Management, 139 (9),1108-1116.
Deb, K., (2001), Multi-objective optimization using evolutionary algorithms, John Wiley & Sons, England.
DeFries JC, Fulker DW., (1985). “Multiple regression analysis of twin data.” Behavior genetics. 15(5):467-73.
Deloitte., (2012). "Key Risks Not Being Continually monitored: Deloitte Survey," Deloitte Development LLC, New York, USA
Denas, S., (2015). “Risk analysis using earned value: An engineering project management study.” International Journal of Risk and Contingency Management (IJRCM), 4(3), 22-33.
Diab, M. F., Varma, A., & Panthi, K. (2017). “Modeling the construction risk ratings to estimate the contingency in highway projects.” Journal of construction engineering and management, 143(8), 04017041.
Diamantas, V.K., Kirytopoulos, K.A. and Leopoulos, V.N., (2011). “Earned value management under risk.” International Journal of Project Organisation and Management, 3(3-4), 335-351.
Dolabi, H. R. Z., Afshar, A., and Abbasnia, R. (2014). “CPM/LOB scheduling method for project deadline constraint satisfaction” Automation in Construction, 48, 107-118.
Drew D, Skitmore M., (1997). “The effect of contract type and size on competitiveness in bidding.” Construction Management & Economics, 15(5):469-89.
Duffy, G. A., Oberlender, G. D., and Seok Jeong, D. H. (2010). “Linear scheduling model with varying production rates” Journal of Construction Engineering and Management, 137 (8), 574-582.
Elbarkouky, M. M., Fayek, A. R., Siraj, N. B., & Sadeghi, N. (2016). “Fuzzy arithmetic risk analysis approach to determine construction project contingency.” Journal of construction engineering and management, 142(12), 04016070.
El-Rayes, K. (2001a). “Object-oriented model for repetitive construction scheduling” Journal of Construction Engineering and Management, 127 (3), 199-205.
El-Rayes, K. (2001b). “Optimum planning of highway construction under A+ B bidding method” Journal of Construction Engineering and Management, 127 (4), 261-269.
El-Rayes, K. A. (1997). “Optimized scheduling for repetitive construction projects.” Ph.D. dissertation, Concordia University, Montreal, Canada
El-Rayes, K., and Moselhi, O. (1998). “Resource-driven scheduling of repetitive activities” Constr. Manage. Econ, 16 (4), 433-446.
El-Rayes, K., and Moselhi, O. (2001). “Optimizing resource utilization for repetitive construction projects” Journal of Construction Engineering and Management, 127 (1), 18-27.
Elshaer, R., (2013). “Impact of sensitivity information on the prediction of project's duration using earned schedule method.” International Journal of Project Management, 31(4), 579-588.
Emsley, M.W., Lowe, D.J., Duff, A.R., Harding, A. and Hickson, A., (2002). “Data modelling and the application of a neural network approach to the prediction of total construction costs.” Construction Management & Economics, 20(6), 465-472.
Fan, S. L., and Lin, Y. C. (2007). “Time-cost trade-off in repetitive projects with soft logic.” Computing in Civil Engineering, ASCE, Reston, VA, 83–90
Fan, S. L., Sun, K. S., and Wang, Y. R. (2012). “GA optimization model for repetitive projects with soft logic” Automation in Construction, 21, 253-261.
Firouzi, A., Yang, W., & Li, C. Q. (2016). “Prediction of total cost of construction project with dependent cost items.” Journal of Construction Engineering and Management, 142(12), 04016072.
Fleming, Q.W. and Koppelman, J.M., (2004). “If EVM is so good... why isn’t it used on all projects.” The Measurable News, 1-5.
Forbes, D., Smith, S. and Horner, M., (2008). “Tools for selecting appropriate risk management techniques in the built environment.” Construction Management and economics, 26(11), 1241-1250.
Friedman, L., (1956). “A competitive-bidding strategy.” Operations research, 4(1), 104-112.
Gates, M., (1967). “Bidding strategies and probabilities.” Journal of the Construction Division, 93(1), 75-110.
Georgy, M. E. (2008). “Evolutionary resource scheduler for linear projects” Automation in Construction, 17 (5), 573-583.
Ghanbari, A., Taghizadeh, H. and Iranzadeh, S., (2017a). “Project duration performance measurement by fuzzy approach under uncertainty.” European Journal of Pure and Applied Mathematics, 10(5), 1135-1147.
Ghanbari, A., Taghizadeh, H. and Iranzadeh, S., (2017b). “A fuzzy approach for measuring project performance based on relative preference relation.” Industrial Engineering & Management Systems, 16(4), 486-494.
Hammad, M. W., Abbasi, A., & Ryan, M. J. (2016). “Allocation and management of cost contingency in projects.” Journal of Management in Engineering, 32(6), 04016014.
Hamzeh, A.M., Mousavi, S.M. and Gitinavard, H., (2020). “Imprecise earned duration model for time evaluation of construction projects with risk considerations.” Automation in Construction, 111, 102993.
Hatefi, S.M., Tamošaitienė, J., (2019). “An integrated fuzzy DEMATEL-fuzzy ANP model for evaluating construction projects by considering interrelationships among risk factors.” Journal of Civil Engineering and Management, 25, 114–131.
Hegazy TM., (1993). “Integrated bid preparation with emphases on risk assessment using neural Networks” PhD thesis, Concordia University, Montreal, Canada.
Hegazy, T. (1999). “Optimization of construction time-cost trade-off analysis using genetic algorithms” Canadian Journal of Civil Engineering, 26 (6), 685-697.
Hegazy, T., and Kamarah, E. (2008). “Efficient repetitive scheduling for high-rise construction” Journal of Construction Engineering and Management, 134 (4), 253-264.
Hegazy, T., and Wassef, N. (2001). “Cost optimization in projects with repetitive nonserial activities” Journal of Construction Engineering and Management, 127 (3), 183-191.
Hegazy, T., Elhakeem, A., and Elbeltagi, E. (2004). “Distributed scheduling model for infrastructure networks” Journal of Construction Engineering and Management, 130 (2), 160-167.
Henderson, K., (2003). “Earned schedule: A breakthrough extension to earned value theory? A retrospective analysis of real project data.” The Measurable News, 1(2), 13-23.
Henderson, K., (2004). “Further developments in earned schedule.” The measurable news, 1(1), 15-22.
Hoseini, E., Hertogh, M., Bosch-Rekveldt, M., (2019). “Developing a generic risk maturity model (GRMM) for evaluating risk management in construction projects.” Journal of Risk Research. 2019, 1–20.
Huang, R. Y., and Sun, K. S. (2006). “Non-unit-based planning and scheduling of repetitive construction projects” Journal of construction engineering and management, 132 (6), 585-597.
Huang, Y., Zou, X., and Zhang, L. (2016). “Genetic algorithm–based method for the deadline problem in repetitive construction projects considering soft logic” Journal of Management in Engineering, 32 (4), 04016002.
Hyari, K. H., El‐Rayes, K., and El‐Mashaleh, M. (2009). “Automated trade‐off between time and cost in planning repetitive construction projects” Construction Management and Economics, 27 (8), 749-761.
Hyari, K., and El-Rayes, K. (2006). “Optimal planning and scheduling for repetitive construction projects” Journal of Management in Engineering, 22 (1), 11-19.
Idrus, A., Fadhil Nuruddin, M., and Rohman, M. A., (2011) “Development of Project Cost Contingency Estimation Model Using Risk Analysis and Fuzzy Expert System.” Journal of Expert Systems with Application, 38(3), 1501–1508
Ipsilandis, P. G. (2007). “Multiobjective linear programming model for scheduling linear repetitive projects” Journal of Construction Engineering and Management, 133 (6), 417-424.
IRM., (2002). “A Risk Management Standard, The Institute of Risk Management.” London, UK, The Association of Insurance and Risk Managers (AIRMIC): London, UK, ALARM The National Forum for Risk Management in the Public Sector: Devon, UK.
Islam, M.S., Nepal, M.P., Skitmore, M., Attarzadeh, M. (2017). “Current research trends and application areas of fuzzy and hybrid methods to the risk assessment of construction projects.” Advanced Engineering Informatics, 33, 112–131.
ISO 31000., (2018). “Risk Management–Guidelines.” International Organization for Standardization. Geneva, Switzerland.
Jang J-S., (1993). “ANFIS: adaptive-network-based fuzzy inference system.” IEEE transactions on systems, man, and cybernetics. 23(3):665-85.
Jia, G., Ni, X., Chen, Z., Hong, B., Chen, Y., Yang, F., Lin, C., (2013). “Measuring the maturity of risk management in large-scale construction projects.” Automation in. Construction, 34, 56–66.
Jugdev, K., Thomas, J., (2002). “From operational process to strategic asset: The evolution of project management's value in organizations.” In Proceedings of the Project Management Institute 33rd Annual Symposium and Conference, San Antonio, TX, USA
Jumas, D., Mohd-Rahim, F.A., Zainon, N. and Utama, W.P., (2018). “Improving accuracy of conceptual cost estimation using MRA and ANFIS in Indonesian building projects.” Built Environment Project and Asset Management. 8 (4), 348-357.
Jung, J. H., Kim, D. Y., & Lee, H. K. (2016). “The computer-based contingency estimation through analysis cost overrun risk of public construction project.” KSCE Journal of Civil Engineering, 20(4), 1119-1130.
Kamyabniya, A. and Bagherpour, M., (2014). “Risk-based earned value management: a novel perspective in software engineering.” International Journal of Industrial and Systems Engineering, 17(2), 170-185.
Khamooshi, H. and Abdi, A., (2017). “Project duration forecasting using earned duration management with exponential smoothing techniques.” Journal of management in engineering, 33(1), 04016032.
Khamooshi, H. and Golafshani, H., (2014). “EDM: Earned Duration Management, a new approach to schedule performance management and measurement.” International Journal of Project Management.
Khesal, T., Saghaei, A., Khalilzadeh, M., Galankashi, M.R. and Soltani, R., (2019). “Integrated cost, quality, risk and schedule control through earned value management (EVM).” Journal of Engineering, Design and Technology, 17(1), 183-203.
Khodakarami, V. and Abdi, A., (2014). “Project cost risk analysis: A Bayesian networks approach for modeling dependencies between cost items.” International Journal of Project Management, 32(7), 1233-1245.
Kim, K., Walewski, J., and Cho, Y. K. (2015). “Multiobjective construction schedule optimization using modified niched pareto genetic algorithm” Journal of Management in Engineering, 32 (2), 04015038.
Kişi Ö., (2007). “Streamflow forecasting using different artificial neural network algorithms.” Journal of Hydrologic Engineering. 12(5), 532-9.
Konak, A., Coit, D.W. and Smith, A.E., (2006). “Multi-objective optimization using genetic algorithms: A tutorial” Reliability Engineering & System Safety, 91 (9), 992-1007.
Lam, T. Y., & Siwingwa, N. (2017). “Risk management and contingency sum of construction projects.” Journal of Financial Management of Property and Construction, 22(3), 237-251.
Leung, Y. F., Liu, W., Lei, Y., & Hsu, S. C. (2018). “Quantifying cost-effectiveness of subsurface strata exploration in excavation projects through geostatistics and spatial tessellation.” Automation in Construction, 90, 243-252.
Lhee, S. C., Flood, I., & Issa, R. R. (2014). “Development of a two-step neural network-based model to predict construction cost contingency.” Journal of Information Technology in Construction (ITcon), 19(24), 399-411.
Lipke, W., (2003). “Schedule is different.” The Measurable News, 31(4), 31-34.
Lipke, W., Zwikael, O., Henderson, K. and Anbari, F., (2009). “Prediction of project outcome: The application of statistical methods to earned value management and earned schedule performance indexes.” International journal of project management, 27(4), 400-407.
Liu, M. and Ling, Y.Y., (2005). “Modeling a contractor’s markup estimation.” Journal of construction engineering and management, 131(4), 391-399.
Liu, S. S., and Wang, C. J. (2007). “Optimization model for resource assignment problems of linear construction projects.” Automation in Construction, 16 (4), 460-473.
Liu, J., Li, B., Lin, B. and Nguyen, V., (2007). “Key issues and challenges of risk management and insurance in China's construction industry.” Industrial Management & Data Systems. Vol. 107 No. 3, pp. 382-396
Lo W, Lin C, Yan M., (2007). “Contractor’s opportunistic bidding behavior and equilibrium price level in the construction market.” Journal of Construction Engineering and Management, 133(6):409-16.
Long, L. D., and Ohsato, A. (2009). “A genetic algorithm-based method for scheduling repetitive construction projects” Automation in Construction, 18 (4), 499-511.
Lucko, G. (2010). “Integrating efficient resource optimization and linear schedule analysis with singularity functions” Journal of construction engineering and management, 137 (1), 45-55.
Marler, R. T., and Arora, J. S. (2010). “The weighted sum method for multi-objective optimization: new insights” Structural and multidisciplinary optimization, 41 (6), 853-862.
Moradi, N., Mousavi, S.M. and Vahdani, B., (2018). “An Interval Type-2 Fuzzy Model for Project-earned Value Analysis Under Uncertainty.” Journal of Multiple-Valued Logic & Soft Computing, 30(1), 79-103
Mortaji, S.T.H., Noori, S., Noorossana, R. and Bagherpour, M., (2018). “An ex ante control chart for project monitoring using earned duration management observations.” Journal of Industrial Engineering International, 14(4), 793-806.
Moselhi O, Hegazy T, Fazio P., (1991). “Neural networks as tools in construction.” Journal of Construction Engineering and Management. 117(4), 606-25.
Moselhi O, Hegazy T, Fazio P., (1993). “DBID: analogy-based DSS for bidding in construction.” Journal of Construction Engineering and Management, 119(3), 466-79.
Moselhi O, Siqueira I., (1998). “Neural networks for cost estimating of structural steel buildings.” AACE International Transactions. IT22.
Moselhi, O. (1997). “Risk assessment and contingency estimating.” AACE International transactions, 90.
Moselhi, O., (2011). “The Use of Eraned Value in Forcasting Project Durations.” Proceedings of the 28th International association for Automation and Robotic in Construction.
Moselhi, O., and El-Rayes, K. (1993a). “Least cost scheduling for repetitive projects” Canadian journal of civil engineering, 20 (5), 834-843.
Moselhi, O., and El-Rayes, K. (1993b). “Scheduling of repetitive projects with cost optimization” Journal of Construction Engineering and Management, 119 (4), 681-697.
Moselhi, O., and Hassanein, A. (2003). “Optimized scheduling of linear projects” Journal of Construction Engineering and Management, 129 (6), 664-673.
Moselhi, O., Dimitrov, B., & Touran, A. (1993). “Monte Carlo technique with correlated random variables, Discussion. Closure.” Journal of construction engineering and management, 119(3), 658-661.
Moselhi, O., Roghabadi, M.A., (2020). “Risk quantification using fuzzy-based Monte Carlo simulation.” Journal of Information Technology in Construction (ITcon), 25, 87–98.
Narbaev, T. and De Marco, A., (2014). “An earned schedule-based regression model to improve cost estimate at completion.” International Journal of Project Management.
Nassar, K. (2011). “Evolutionary optimization of resource allocation in repetitive construction schedules” Journal of Information Technology in Construction, 10 (18), 265-273.
Ok SC, Sinha SK., (2006). “Construction equipment productivity estimation using artificial neural network model.” Construction Management and Economics. 24(10), 1029-44.
Okmen, Ö., & Öztaş, A. (2010). “Construction cost analysis under uncertainty with correlated cost risk analysis model.” Journal of Construction Management and Economics, 28(2), 203-212.
Olumide, A. O., Anderson, S. D., & Molenaar, K. R. (2010). “Sliding-scale contingency for project development process.” Transportation Research Record, 2151(1), 21-27.
Paige, H.W., (1963). “How PERT-cost helps the general manager.” Harvard Business Review, 41(6), 87-95.
Pajares, J. and Lopez-Paredes, A., (2011). “An extension of the EVM analysis for project monitoring: The Cost Control Index and the Schedule Control Index.” International Journal of Project Management, 29(5), 615-621.
Palisade Corporation, (2015) “Evolver user’s guide: the genetic algorithm solver for Microsoft excel” Version 7, Palisade Corporation, Ithaca, NY.
Perera, S. (1983). “Resource sharing in linear construction” Journal of Construction Engineering and Management, 109 (1), 102-111.
PMI., (2008). “Organizational Project Management Maturity Model (OPM3)” Project Management Institute: Newtown Square, PA, USA,
PMI., (2009). “Practice Standard for Project Risk Management.” Project Management Institute: Newtown Square, PA, USA.
PMI., (2017). “A Guide to the Project Management Body of Knowledge (PMBOK Guide).” 6th ed., Project Management Institute: Newtown Square, PA, USA.
PMI., Pulse of the Profession® report., (2015). “Capturing the Value of project management.” Project Management Institute: Newtown Square, PA, USA.
Polat G, Bingol BN, Gurgun AP, Yel B.,(2016). “Comparison of ANN and MRA Approaches to Estimate Bid Mark-up Size in Public Construction Projects.” Procedia Engineering, 164, 331-338.
Popic, Z., Moselhi, O., (2014). “Project Delivery Systems Selection for Capital Projects Using the Analytical Hierarchy Process and the Analytical Network Process.” In Proceedings of the Construction Research Congress 2014: Construction in a Global Network, Atlanta, Georgia , USA, 1339–1348.
Puri D, Tiwari S., (2014). “Evaluating the criteria for contractors’ selection and bid evaluation.” International Journal of Engineering Science Invention, 3(7), 44-8.
Reeves CR., (1993) “Modern heuristic techniques for combinatorial problems” John Wiley & Sons, Inc.
Roghabadi, M.A. and Moselhi, O., (2019). “Optimized acceleration in linear scheduling”. Canadian Society for Civil Engineering (CSCE) Annual Conference, Laval, Canada.
Roghabadi, M.A. and Moselhi, O., (2018). “Three Models for Estimating Bid Markups” 2018 AACE® International Transactions, EST.2884.1, California, USA.
Roghabadi, M.A. and Moselhi, O., (2020a). “A Fuzzy-Based Decision Support Model for Risk Maturity Evaluation of Construction Organizations.” Algorithms, 13(5), p.115.
Roghabadi, M.A. and Moselhi, O., (2020c). “Forecasting Project Duration Using Risk-Based Earned Duration Management” International Journal of Construction Managemen, Under review.
Roghabadi, M.A. and Moselhi, O., (2020b). “Optimized crew selection for scheduling of repetitive projects.” Engineering, Construction and Architectural Management. Vol. ahead-of-print No. ahead-of-print.
Roghanian, E., Alipour, M. and Rezaei, M., (2018). “An improved fuzzy critical chain approach in order to face uncertainty in project scheduling.” International Journal of Construction Management, 18(1), 1-13.
Russell, A. D., and Caselton, W. F. (1988). “Extensions to linear scheduling optimization” Journal of Construction Engineering and Management, 114 (1), 36-52.
Saaty, T.L., (2004) “Decision making—The analytic hierarchy and network processes (AHP/ANP).” Journal of systems science and systems engineering, 13, 1–35.
Saaty, T.L., Özdemir, M.S., Saaty, T.L., (2005) “The Encyclicon: A Dictionary of Decisions with Dependence and Feedback Based on the Analytic Network Process” RWS Publications: Pittsburgh, PA, USA, Volume 292.
Sadeghi, N., Fayek, A.R. and Pedrycz, W., (2010). “Fuzzy Monte Carlo Simulation and Risk Assessment in Construction.” Journal of Computer-Aided Civil and Infrastructure Engineering, 25 (4), 238-252,
Salah, A. (2012). “Fuzzy Set-Based Contingency Estimating and Management.” Master of Applied Science dissertation, Concordia University.
Salah, A. and Moselhi, O., (2016). “Risk identification and assessment for engineering procurement construction management projects using fuzzy set theory.” Canadian Journal of Civil Engineering, 43(5), 429-442.
Salah, A., (2015). “Fuzzy Set-Based Risk Management for Construction Projects.” Ph.D. Thesis, Concordia University, Montreal, QC, Canada,
Salah, A., and Moselhi, O. (2015). “Contingency modelling for construction projects using fuzzy-set theory” Engineering, Construction and Architectural Management, 22 (2), 214-241.
Salama, T., and Moselhi, O. (2019). “Multi-Objective Optimization for Repetitive Scheduling under Uncertainty” Engineering, Construction and Architectural Management, 26 (7), 1294-1320.
Salama, T., Salah, A., and Moselhi, O. (2017). “Integration of linear scheduling method and the critical chain project management” Canadian Journal of Civil Engineering, 45 (1), 30-40.
Selinger, S. (1980). “Construction planning for linear projects” Journal of the Construction Division, 106 (2), 195-205.
Senouci, A. B., and Eldin, N. N. (2004). “Use of genetic algorithms in resource scheduling of construction projects” Journal of Construction Engineering and Management, 130 (6), 869-877.
Seydel, J. and Olson, D.L., (1990). “Bids considering multiple criteria.” Journal of Construction Engineering and Management, 116(4), 609-623.
Shaheen, A. A., Fayek, A. R., and AbouRizk, S. M. (2007). “Fuzzy numbers in cost range estimating” Journal of Construction Engineering and Management, 133 (4), 325-334.
Shaheen, A., Robinson, A. F. and Aburizk, S. M., (2007). “Fuzzy Numbers in Cost Range Estimating.” Journal of Construction Engineering and Management, 133 (4), 325-334.
Smith, G. R., & Bohn, C. M. (1999). “Small to medium contractor contingency and assumption of risk.” Journal of construction engineering and management, 125(2), 101-108.
Soetanto R, Proverbs DG., (2004). “Intelligent models for predicting levels of client satisfaction.” Journal of construction Research. 5(2), 233-53.
Suhail, S. A., and Neale, R. H. (1994). “CPM/LOB: New methodology to integrate CPM and line of balance” Journal of Construction Engineering and Management, 120 (3), 667-684.
Super Decisions Tutorials., (2020) “Tutorial 04: Changing from AHP to ANP.” Super Decisions. Available online: URL https://superdecisions.com/tutorials/index.php?section=v28_tut04 (accessed March 2020)
Tabriz, A.A., Farrokh, M., Nooshabadi, G.M. and Nia, H.H., (2013). “A combined approach of the earned value management and the risk management for estimating final results of projects in fuzzy environment.” Business Management and Strategy, 4(1), 32-52.
Tavakoli, A. and Utomo, J., (1989). “Bid markup assistant: An expert system.” Cost Engineering, 31(6), 28.
Touran, A. (1993). “Probabilistic cost estimating with subjective correlations.” Journal of Construction Engineering and Management, 119(1), 58-71.
Touran, A., & Suphot, L. (1997). “Rank correlations in simulating construction costs.” Journal of construction engineering and management, 123(3), 297-301.
Touran, A., and Wiser, E. (1992). “Monte Carlo Technique with Correlated Random Variables.” Journal of Construction Engineering and Management, 11 (2), 258-272,
Vandevoorde, S. and Vanhoucke, M., (2006). “A comparison of different project duration forecasting methods using earned value metrics.” International journal of project management, 24(4), 289-302.
Vanhoucke, M. (2006). “Work continuity constraints in project scheduling” Journal of Construction Engineering and Management, 132 (1), 14-25.
Vanhoucke, M., (2017). “Combining EDM and EVM: a developed simplification for project time and cost management.” Journal of Modern Project Management, 5(2), 94-107.
Vanhoucke, M., Andrade, P., Salvaterra, F. and Batselier, J., (2015). Introduction to Earned Duration. The Measurable News, (2), 15-27.
Vorster, M. C., and Bafna, T. (1992). “Discussion of “Formal Development of Line-of-Balance Technique” by Zohair M. Al Sarraj (December, 1990, Vol. 116, No. 4).” Journal of Construction Engineering and Management. Manage, 118 (1), 210-211.
Votto, R., Lee Ho, L. and Berssaneti, F., (2020). “Applying and Assessing Performance of Earned Duration Management Control Charts for EPC Project Duration Monitoring.” Journal of Construction Engineering and Management, 146(3), p.04020001.
Wall, D. M., (1997). “Distributions and Correlations in Monte Carlo Simulation.” Journal of Construction Management and Economics, 15 (3), 241-258,
Wibowo, A., and Taufik, J., (2017). “Developing a self-assessment model of risk management maturity for client organizations of public construction projects” Indonesian context. Procedia Engineering, 171, 274–281.
Wood, D.A., (2018). “A critical-path focus for earned duration increases its sensitivity for project-duration monitoring and forecasting in deterministic, fuzzy and stochastic network analysis.” Journal of Computational Methods in Sciences and Engineering, 18(2), 359-386.
Xia, B., Chan, A.P., Yeung, J.F., (2011). “Developing a fuzzy multicriteria decision-making model for selecting design-build operational variations.” Journal of construction engineering and management, 137, 1176–1184.
Yang, I. T. (2005). “Simulation-based estimation for correlated cost elements.” International Journal of Project Management, 23(4), 275-282
Yeo, K. T. (1990). “Risks, classification of estimates, and contingency management.” Journal of Management in Engineering, 6(4), 458-470.
Zafar, I., Wuni, I.Y., Shen, G.Q., Ahmed, S. and Yousaf, T., (2019). “A fuzzy synthetic evaluation analysis of time overrun risk factors in highway projects of terrorism-affected countries: the case of Pakistan.” International Journal of Construction Management, 1-19.
Zhao, X., Hwang, B.G., Low, S.P., (2013). “Developing fuzzy enterprise risk management maturity model for construction firms.” Journal of Construction Engineering and Management, 2013, 139, 1179–1189.
Zhao, X., Hwang, B.G., Low, S.P., (2014). “Investigating enterprise risk management maturity in construction firms.” Journal of Construction Engineering and Management, 140, 05014006.
Zou, P.X., Chen, Y., Chan, T.Y., (2010). “Understanding and improving your risk management capability: Assessment model for construction organizations.” Journal of Construction Engineering and Management,136, 854-863.
Zou, X., Zhang, Q., and Zhang, L. (2017). “Modeling and solving the deadline satisfaction problem in line-of-balance scheduling” Journal of Management in Engineering, 34 (1), 04017044
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