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Arditi, D and Balci, G (2009) Managerial Competencies of Female and Male Construction Managers. Journal of Construction Engineering and Management, 135(11), 1275–8.
Cable, J K, Jaselskis, E J, Walters, R C, Li, L and Bauer, C R (2009) Stringless Portland Cement Concrete Paving. Journal of Construction Engineering and Management, 135(11), 1253–60.
Caerteling, J S, Halman, J I M, Song, M and Dorée, A G (2009) Impact of Government and Corporate Strategy on the Performance of Technology Projects in Road Construction. Journal of Construction Engineering and Management, 135(11), 1211–21.
Chan, A P C, Chan, D W M and Yeung, J F Y (2009) Overview of the Application of “Fuzzy Techniques” in Construction Management Research. Journal of Construction Engineering and Management, 135(11), 1241–52.
Chan, A P C, Lam, P T I, Chan, D W M, Cheung, E and Ke, Y (2009) Drivers for Adopting Public Private Partnerships—Empirical Comparison between China and Hong Kong Special Administrative Region. Journal of Construction Engineering and Management, 135(11), 1115–24.
Chen, C and Orr, R J (2009) Chinese Contractors in Africa: Home Government Support, Coordination Mechanisms, and Market Entry Strategies. Journal of Construction Engineering and Management, 135(11), 1201–10.
Chen, H L (2009) Model for Predicting Financial Performance of Development and Construction Corporations. Journal of Construction Engineering and Management, 135(11), 1190–200.
El-Rayes, K and Jun, D H (2009) Optimizing Resource Leveling in Construction Projects. Journal of Construction Engineering and Management, 135(11), 1172–80.
Goh, Y M and Chua, D K H (2009) Case-Based Reasoning for Construction Hazard Identification: Case Representation and Retrieval. Journal of Construction Engineering and Management, 135(11), 1181–9.
Gransberg, D D and Riemer, C (2009) Impact of Inaccurate Engineer’s Estimated Quantities on Unit Price Contracts. Journal of Construction Engineering and Management, 135(11), 1138–45.
Lee, H, Seo, J, Park, M, Ryu, H and Kwon, S (2009) Transaction-Cost-Based Selection of Appropriate General Contractor-Subcontractor Relationship Type. Journal of Construction Engineering and Management, 135(11), 1232–40.
Park, M, Ji, S, Lee, H and Kim, W (2009) Strategies for Design-Build in Korea Using System Dynamics Modeling. Journal of Construction Engineering and Management, 135(11), 1125–37.
Park, S H (2009) Whole Life Performance Assessment: Critical Success Factors. Journal of Construction Engineering and Management, 135(11), 1146–61.
Park, T, Kim, M K, Kim, C and Kim, H (2009) Interactive 3D CAD for Effective Derrick Crane Operation in a Cable-Stayed Bridge Construction. Journal of Construction Engineering and Management, 135(11), 1261–70.
San Cristóbal, J R (2009) Time, Cost, and Quality in a Road Building Project. Journal of Construction Engineering and Management, 135(11), 1271–4.
Wethyavivorn, P, Charoenngam, C and Teerajetgul, W (2009) Strategic Assets Driving Organizational Capabilities of Thai Construction Firms. Journal of Construction Engineering and Management, 135(11), 1222–31.
Zahraie, B and Tavakolan, M (2009) Stochastic Time-Cost-Resource Utilization Optimization Using Nondominated Sorting Genetic Algorithm and Discrete Fuzzy Sets. Journal of Construction Engineering and Management, 135(11), 1162–71.
- Type: Journal Article
- Keywords: Optimization; Costs; Resource allocation; Stochastic processes; Fuzzy sets; Scheduling; Construction management;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000092
- Abstract:
In a construction project, the cost and duration of activities could change due to different uncertain variables such as weather, resource availability, etc. Resource leveling and allocation strategies also influence total time and costs of projects. In this paper, two concepts of time-cost trade-off and resource leveling and allocation have been embedded in a stochastic multiobjective optimization model which minimizes the total project time, cost, and resource moments. In the proposed time-cost-resource utilization optimization (TCRO) model, time and cost variables are considered to be fuzzy, to increase the flexibility for decision makers when using the model outputs. Application of fuzzy set theory in this study helps managers/planners to take these uncertainties into account and provide an optimal balance of time, cost, and resource utilization during the project execution. The fuzzy variables are discretized to represent different options for each activity. Nondominated sorting genetic algorithm (NSGA-II) has been used to solve the optimization problem. Results of the TCRO model for two different case studies of construction projects are presented in the paper. Total time and costs of the two case studies in the Pareto front solutions of the TCRO model cover more than 85% of the ranges of total time and costs of solutions of the biobjective time-cost optimization (TCO) model. The results show that adding the resource leveling capability to the previously developed TCO models provides more practical solutions in terms of resource allocation and utilization, which makes this research relevant to both industry practitioners and researchers.