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Biswas, P K, Khan, S M, Piratla, K and Chowdhury, M (2023) Development and evaluation of statistical and machine-learning models for queue-length estimation for lane closures in freeway work zones. Journal of Construction Engineering and Management, 149(05).

Chong, H Y and Cheng, M (2023) Smart contract implementation in building information modeling-enabled projects: Approach to contract administration. Journal of Construction Engineering and Management, 149(05).

Ding, S, Hu, H, Dai, L and Wang, W (2023) Blockchain adoption among multi-stakeholders under government subsidy: From the technology diffusion perspective. Journal of Construction Engineering and Management, 149(05).

Feng, Z, Chao, Q, Tan, C and Yang, Y (2023) Using bargaining model with loss aversion and a risk of breakdown to determine compensation for buyback of early terminating BOT highway projects. Journal of Construction Engineering and Management, 149(05).

Garg, S and Misra, S (2023) Framework for estimating quality-related incentive and disincentive in construction projects. Journal of Construction Engineering and Management, 149(05).

Gonsalves, N, Akanmu, A, Gao, X, Agee, P and Shojaei, A (2023) Industry perception of the suitability of wearable robot for construction work. Journal of Construction Engineering and Management, 149(05).

Han, S, Jiang, Y, Huang, Y, Wang, M, Bai, Y and Spool-White, A (2023) Scan2drawing: Use of deep learning for as-built model landscape architecture. Journal of Construction Engineering and Management, 149(05).

Jung, H, Seo, W and Kang, Y (2023) Differences in workers' safety behavior by project size and risk level of work in South Korea. Journal of Construction Engineering and Management, 149(05).

Labik, O, Nahmens, I, Ikuma, L and Harvey, C (2023) On-site versus in-factory installation of solar-plus-storage in modular construction. Journal of Construction Engineering and Management, 149(05).

Saqib, G, Hassan, M U, Zubair, M U and Choudhry, R M (2023) Investigating the acceptance of an electronic incident reporting system in the construction industry: An application of the technology acceptance model. Journal of Construction Engineering and Management, 149(05).

Shen, K, Zhu, Y, Pan, J and Li, X (2023) An intelligent decision-making model for the design of precast slab joints based on case-based reasoning. Journal of Construction Engineering and Management, 149(05).

Ullal, A (2023) Construction conditions and practices during war in Afghanistan. Journal of Construction Engineering and Management, 149(05).

Wang, C, Zhang, S, Gao, Y, Guo, Q and Zhang, L (2023) Effect of contractual complexity on conflict in construction subcontracting: Moderating roles of contractual enforcement and organizational culture distance. Journal of Construction Engineering and Management, 149(05).

Wang, J, Han, C and Li, X (2023) Modified streamlined optimization algorithm for time-cost tradeoff problems of complex large-scale construction projects. Journal of Construction Engineering and Management, 149(05).

  • Type: Journal Article
  • Keywords: critical path identification method; integer programming; network analysis; optimization; time-cost tradeoff
  • ISBN/ISSN: 0733-9364
  • URL: http://doi.org/10.1061/JCEMD4.COENG-12970
  • Abstract:
    Although research on time-cost tradeoff (TCT) problems has been extensively conducted, there are still few applications of TCT optimization methods in the scheduling of projects with practical size and complexity. As a good attempt, a streamlined optimization algorithm has recently been developed for solving TCT problems with a continuous curvilinear activity time-cost relationship. However, the algorithm encounters the difficulties of high memory requirements and computational demand when it is implemented in complex large-scale projects whose networks may involve tens of millions of paths and hundreds of activities. To overcome such difficulties, this study presents a modified version of the streamlined optimization algorithm. Particularly, a new method for identifying critical paths is proposed in the modified algorithm. Also, a modeling problem has been addressed in order to consolidate the theoretical foundation of the algorithm. As illustrated by the experimental examples, the modified streamlined algorithm outperforms the original algorithm and the commonly used genetic algorithm in terms of optimality, robustness, and computational efficiency. This study thus contributes to the development of commercial scheduling software capable of tackling practical TCT problems.

Xue, G, Liu, S, Ren, L and Gong, D (2023) Adaptive cross-scenario few-shot learning framework for structural damage detection in civil infrastructure. Journal of Construction Engineering and Management, 149(05).

Zhang, Y, Minchin, R E, Flood, I and Ries, R J (2023) Preliminary cost estimation of highway projects using statistical learning methods. Journal of Construction Engineering and Management, 149(05).

Zhou, Y, Wang, X, Gosling, J and Naim, M M (2023) The system dynamics of engineer-to-order construction projects: Past, present, and future. Journal of Construction Engineering and Management, 149(05).