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Alanjari, P, RazaviAlavi, S and AbouRizk, S (2015) Hybrid Genetic Algorithm-Simulation Optimization Method for Proactively Planning Layout of Material Yard Laydown. Journal of Construction Engineering and Management, 141(10).

de Athayde Prata, B, Pitombeira-Neto, A R and de Moraes Sales, C J (2015) An Integer Linear Programming Model for the Multiperiod Production Planning of Precast Concrete Beams. Journal of Construction Engineering and Management, 141(10).

de Oliveira, A L and Prudêncio, L R (2015) Evaluation of the Superficial Texture of Concrete Pavers Using Digital Image Processing. Journal of Construction Engineering and Management, 141(10).

Heravi, G and Eslamdoost, E (2015) Applying Artificial Neural Networks for Measuring and Predicting Construction-Labor Productivity. Journal of Construction Engineering and Management, 141(10).

Ma, G, Gu, L and Li, N (2015) Scenario-Based Proactive Robust Optimization for Critical-Chain Project Scheduling. Journal of Construction Engineering and Management, 141(10).

  • Type: Journal Article
  • Keywords: Scheduling; Duration; Robustness; Scenario; Critical-chain project management (CCPM); Cost and schedule;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001003
  • Abstract:
    The robustness of construction project schedules is a key factor that determines the capability of the schedules in offsetting the negative impact of uncertainties, which are the primary causes of project delays. This paper proposes a scenario-based proactive robustness optimization (SBPRO) method, which aims to improve the robustness of construction project schedules that are developed using the critical-chain project management (CCPM) method. The SBPRO method integrates scenarios that represent all possible situations that may happen during project implementation. Therefore, schedules are less sensitive to variations of situations than schedules developed using the traditional CCPM-based scheduling method. Moreover, the SBPRO method is based on a dual-objective function and optimizes schedules by balancing a trade-off between two objectives, namely, reducing the length of planned schedules and mitigating the uncertainties in schedule execution. The SBPRO method was validated in three case studies. The results showed that the SBPRO method outperformed the traditional CCPM-based scheduling method by generating schedules that could ensure higher probabilities of on-time project completion. The results also demonstrated that the SBPRO method could serve to promote the understanding and acceptance among project teams of the trade-off between project duration and schedule robustness when managing complex construction projects.

Shealy, T and Klotz, L (2015) Well-Endowed Rating Systems: How Modified Defaults Can Lead to More Sustainable Performance. Journal of Construction Engineering and Management, 141(10).

Song, J, Song, D and Zhang, D (2015) Modeling the Concession Period and Subsidy for BOT Waste-to-Energy Incineration Projects. Journal of Construction Engineering and Management, 141(10).