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Akin, F D, Damci, A and Arditi, D (2024) Optimum finance-based scheduling. Journal of Construction Engineering and Management, 150(09).

  • Type: Journal Article
  • Keywords: finance-based scheduling; financing cost; optimal financing models; total float
  • ISBN/ISSN: 0733-9364
  • URL: http://doi.org/10.1061/JCEMD4.COENG-15103
  • Abstract:
    Even though advanced heuristic and metaheuristic models have been developed for minimizing financing cost by using total float to adjust the start times of activities, these models overlook the fact that the attempt to minimize financing cost may result in more than one work schedule with minimum financing cost. It is therefore not surprising that no research has been conducted to select the best financing schedule out of the multiple optimal work schedules. It is well known that total float must be used sparingly to avoid the creation of too many critical and near-critical activities that may cause delays in the project duration. Indeed, the loss of schedule flexibility caused by the use of total float comes at a cost. It is argued in this paper that the cost of float consumption should be a vital part of models designed to minimize financing cost. The research presented in this paper attempts to fill this gap. A model is proposed in this study that not only minimizes financing cost but also demonstrates the negative impact of not considering the cost of float consumption in reaching the optimal solution, an area of research that is mostly overlooked in the finance-based scheduling literature. This research contributes to the body of knowledge by demonstrating that there may be more than one work schedule with minimum financing cost, and that the cost of float consumption must be considered to find the most optimal solution.

Assaad, R H, Omran, A, Soliman, N and Assaf, G (2024) Prediction of the lateral pressure of self-consolidating concrete on construction formwork systems using machine-learning algorithms. Journal of Construction Engineering and Management, 150(09).

Assaf, G and Assaad, R H (2024) Analyzing the critical success factors affecting project bundling performance of infrastructure projects. Journal of Construction Engineering and Management, 150(09).

Chammout, B, El-Adaway, I H, Abdul Nabi, M and Assaad, R H (2024) Price escalation in construction projects: Examining national and international contracts. Journal of Construction Engineering and Management, 150(09).

Dorignon, L, Oswald, D, Kempton, L, Boehme, T, Iyer-Raniga, U, Moore, T and Dalton, T (2024) Investigating residential building materials in a circular economy: An Australian perspective. Journal of Construction Engineering and Management, 150(09).

Görsch, C, Seppänen, O, Peltokorpi, A and Lavikka, R (2024) Unlocking productivity: Revealing waste and hidden disturbances impacting mep workers. Journal of Construction Engineering and Management, 150(09).

Gao, M Y, Han, J, Yang, Y, Tiong, R L K, Zhao, C and Han, C (2024) BIM-based and IoT-driven smart tracking for precast construction dynamic scheduling. Journal of Construction Engineering and Management, 150(09).

Jiang, Y, Yang, G, Li, H, Zhang, T and Khudhair, A (2024) Physics-informed knowledge-driven decision-making framework for holistic bridge maintenance. Journal of Construction Engineering and Management, 150(09).

Koo, H J, Kelly, D and Deman, D (2024) Risk assessment of the challenges in the adaptive reuse of historic buildings. Journal of Construction Engineering and Management, 150(09).

Namian, M, Nabil, F R, Al-Mhdawi, M K S, Kermanshachi, S S and Nnaji, C (2024) Postpandemic era: Investigating the impact of COVID-19 on construction workers' situational awareness. Journal of Construction Engineering and Management, 150(09).

Ning, X, Yang, Y, Liu, C and Han, Y (2024) Construction workers' unsafe behavior contagion under government-contractor dual influence. Journal of Construction Engineering and Management, 150(09).

Olugboyega, O (2024) Diverse forms of greed and self-interest that contribute to corruption among construction stakeholders. Journal of Construction Engineering and Management, 150(09).

Ouyang, Y and Luo, X (2024) Effects of physical fatigue on construction workers' visual search patterns during hazard identification. Journal of Construction Engineering and Management, 150(09).

Paneru, S, Suh, S, Seo, W and Rausch, C (2024) Evaluating the decarbonization potential of industrialized construction: A review of the current state, opportunities, and challenges. Journal of Construction Engineering and Management, 150(09).

Sadoughi, A, Kouhirostami, M, Kouhirostamkolaei, M, Qi, B and Costin, A (2024) Autonomous building design for manufacturing and assembly: A systematic review of design application, challenges, and opportunities. Journal of Construction Engineering and Management, 150(09).

Shahedi, F, Etemadfard, H, Omrani, F and Ghalehnovi, M (2024) Cost performance modeling for steel fabrication shops with machine learning algorithms. Journal of Construction Engineering and Management, 150(09).

Shuang, Q, Liu, X, Wang, Z and Xu, X (2024) Automatically categorizing construction accident narratives using the deep-learning model with a class-imbalance treatment technique. Journal of Construction Engineering and Management, 150(09).

Wang, R D, Zayed, T, Eltoukhy, A E E and Wu, H (2024) Integrated planning approach for optimizing tower crane and truck locations in modular integrated construction. Journal of Construction Engineering and Management, 150(09).

Wu, H, Chang, Y and Chen, Y (2024) Transitioning work arrangements in the construction industry: Changes in time-use patterns and individual greenhouse gas emissions. Journal of Construction Engineering and Management, 150(09).

Yang, J, Wu, Y and Li, D (2024) Block planning based on grid's topology for the dismantling of long-span spatial lattice structures. Journal of Construction Engineering and Management, 150(09).

Zhang, Y, Chang, R, Mao, W, Zuo, J, Liu, L and Han, Y (2024) Challenges of automating interior construction progress monitoring. Journal of Construction Engineering and Management, 150(09).

Zhang, Y, Liu, L, Song, Z, Zhao, Y and He, S (2024) Enhancing tunnel boring machine penetration rate predictions through particle swarm optimization and elman neural networks. Journal of Construction Engineering and Management, 150(09).