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Aljassmi, H, Han, S and Davis, S (2014) Project Pathogens Network: New Approach to Analyzing Construction-Defects-Generation Mechanisms. Journal of Construction Engineering and Management, 140(01).

Casanovas, M d M, Armengou, J and Ramos, G (2014) Occupational Risk Index for Assessment of Risk in Construction Work by Activity. Journal of Construction Engineering and Management, 140(01).

Chang, C (2014) Principal-Agent Model of Risk Allocation in Construction Contracts and Its Critique. Journal of Construction Engineering and Management, 140(01).

Choi, S, Kim, D Y, Han, S H and Kwak, Y H (2014) Conceptual Cost-Prediction Model for Public Road Planning via Rough Set Theory and Case-Based Reasoning. Journal of Construction Engineering and Management, 140(01).

González, P, González, V, Molenaar, K and Orozco, F (2014) Analysis of Causes of Delay and Time Performance in Construction Projects. Journal of Construction Engineering and Management, 140(01).

Laryea, S and Lubbock, A (2014) Tender Pricing Environment of Subcontractors in the United Kingdom. Journal of Construction Engineering and Management, 140(01).

Ling, F Y Y, Ke, Y, Kumaraswamy, M M and Wang, S (2014) Key Relational Contracting Practices Affecting Performance of Public Construction Projects in China. Journal of Construction Engineering and Management, 140(01).

Narbaev, T and De Marco, A (2014) Combination of Growth Model and Earned Schedule to Forecast Project Cost at Completion. Journal of Construction Engineering and Management, 140(01).

Ning, Y and Ling, F Y Y (2014) Boosting Public Construction Project Outcomes through Relational Transactions. Journal of Construction Engineering and Management, 140(01).

Panas, A and Pantouvakis, J P (2014) Simulation-Based and Statistical Analysis of the Learning Effect in Floating Caisson Construction Operations. Journal of Construction Engineering and Management, 140(01).

Rosenfeld, Y (2014) Root-Cause Analysis of Construction-Cost Overruns. Journal of Construction Engineering and Management, 140(01).

Sun, C, Mackley, A and Edara, P (2014) Programmatic Examination of Missouri Incentive/Disincentive Contracts for Mitigating Work Zone Traffic Impacts. Journal of Construction Engineering and Management, 140(01).

Syal, M, Duah, D, Samuel, S, Mazor, M, Mo, Y and Cyr, T (2014) Information Framework for Intelligent Decision Support System for Home Energy Retrofits. Journal of Construction Engineering and Management, 140(01).

Yang, I, Lin, Y and Lee, H (2014) Use of Support Vector Regression to Improve Computational Efficiency of Stochastic Time-Cost Trade-Off. Journal of Construction Engineering and Management, 140(01).

  • Type: Journal Article
  • Keywords: Stochastic processes; Multiple objective analysis; Optimization; Construction costs; Time factors; Time-cost trade-off; Multiobjective optimization; Support vector regression; Particle swarm optimization; Metaheuristic; Uncertainty analysis; Cost and sche
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000784
  • Abstract:
    Stochastic time-cost trade-off has been a popular object of investigation in past decades because there are uncertain factors that can be considered when determining the appropriate trade-off between project completion time and cost. Previous studies, however, have implemented a double loop procedure, which performs optimization in the outer loop and simulation in the inner loop. The double loop procedure is ponderous because it requires an unacceptably long computation time (taking hours or days), even for a small to medium project. The present study proposes an integrated system that converts the double loop to single loops,thereby dramatically reducing computation time. This is done by incorporating a support vector regression model to obtain a decision function, which will be used to replace the time-consuming Monte Carlo simulation to evaluate the objective function values for individual solutions. With the objective function values, a multiobjective particle swarm optimization algorithm is developed to search for the Pareto front composed of nondominated solutions. It has been empirically shown that the proposed system significantly outperforms the conventional double loop procedure because the former can consistently generate a better Pareto front (with a larger hyperarea ratio) hundreds of times faster by using much less computation time. The Student’s t test is performed to validate the superiority of the proposed system. The contribution of the proposed system is multifold. First, improved computational efficiency is essential for the widespread acceptance of the stochastic time-cost trade-off analysis in practical applications. Second, with less computation time spent in simulation, efforts can be focused on the search for much better nondominated solutions. Third, the proposed system can incorporate the risk attitudes of the decision makers into the analysis by allowing them to specify the probability that they can tolerate for project duration (cost) to exceed a certain limit.

Zhang, S, Du, C, Sa, W, Wang, C and Wang, G (2014) Bayesian-Based Hybrid Simulation Approach to Project Completion Forecasting for Underground Construction. Journal of Construction Engineering and Management, 140(01).