ACADEMIA Letters Modeling in project planning & scheduling in construction management and project time optimization Shakib Zohrehvandi, New Technologies department, Center for European Studies, Kharazmi University, Tehran, Iran These days, one of the biggest problems that companies and organizations are faced with is that their projects take longer than the scheduled duration. An effective method to improve the stability of project scheduling is to consider buffers to cope with time changes of projects using the critical chain method. To increase safety in project implementation and factories production in the face of possible and unpredictable events, time buffers will be placed in different parts of projects and activities to prevent the negative effects of fluctuations in activities on the project’s critical chain which will otherwise lead to a delay in the whole project. Three types of buffers are used, called the Project Buffer, Feeding Buffer, and Resource Buffer (Vanhoucke et al., 2016). The project buffer is placed at the end of the project’s critical chain to maintain the project delivery date (Goldratt, 1997). Buffer management can be considered as the most important measure in implementing the critical chain scheduling, because if short buffers are allotted, we will need to re-schedule the project repeatedly until the end of the project, and if long buffers are allotted, all concepts used in scheduling will be violated (Zohrehvandi et al., 2020). According to an extensive study by Hall (2015), project scheduling and project buffer management are among research areas with a high research potential for the next 10 years. The critical chain project management (CCPM) technique improves the accuracy of project plans by addressing variations by considering buffers in the project schedule. CCPM was originally proposed by Goldratt (1997) in an attempt to improve the traditional methods of project management using a new mechanism to manage uncertainties. The Theory of Constraints (TOC) and the critical chain/buffer management are two effective approaches in project management (Goldratt, 1984). Since the introduction of the TOC, several researchers have examined its Academia Letters, January 2022 ©2022 by the author — Open Access — Distributed under CC BY 4.0 Corresponding Author: Shakib Zohrehvandi, shakibzohrevandi@gmail.com Citation: Zohrehvandi, S. (2022). Modeling in project planning & scheduling in construction management and project time optimization. Academia Letters, Article 4765. https://doi.org/10.20935/AL4765. 1 application in project management (e.g. Newbold (1998), Herroelen and Leus (2001), Leach (2005), Tukel et al. (2006), Woeppel (2006), Rabbani et al. (2007), Blackstone et al. (2009)). Project buffer and feeding buffers aggregate the protection (by removing the safety from the individual tasks) that a project needs to meet its due date and allow focus on project duration (Leach, 2005). To deliver a project within the shortest possible time, several project planning and scheduling techniques such as CCPM can typically be used in project implementation (Li et al, 2019). CCPM technique identifies the longest chain of both precedence and resource-dependent tasks in the generated project schedule as the critical chain of the project network schedule. CCPM is based on methods and algorithms derived from TOC. Most traditional methods of buffer sizing such as root square error method (RSEM), cut and paste method (C&PM), adaptive procedure with resource tightness (APRT), and adaptive procedure with density (APD) do not yield realistic buffer estimations under resource constraints (Vanhoucke, 2016). To improve this problem, it’s better to hybrid these methods with other scheduling methods or designs a new project buffer management algorithm/model. Hu et al. (2017) developed an improved framework for buffer management based on the critical chain, which allowed for additional resources to be allocated if need be. Sarkar et al. (2018) focused on construction projects and developed a project management framework based on the critical chain. Hu et al. (2019) presented six prioritization indices for selecting an optimal chain when more than one chain is possible. Then, they examined four production plans for rescheduling. She et al. (2021) proposed a new procedure for buffer sizing based on network decomposition, which offers logical advantages over previous ones. In this research, the size of a feeding buffer is determined from all associated noncritical chains. Then, the project buffer incorporates safety margins outside the critical chain by comparing feeding chains with their parallel critical counterparts. Zohrehvandi and Khalilzadeh (2019) integrated the APRT method with Failure Modes and Effects Analysis (FMEA), which resulted in a shorter project duration. Zohrehvandi et al. (2020) introduced a heuristic algorithm to determine the sizes of project buffer and feeding buffers as well as dynamically control buffer consumption, named Fuzzy Overlapping Buffer Management Algorithm (FOBMA). In the research, the pentagonal fuzzy numbers were used to determine the appropriate amount of project activity resources. Also, an overlapping method was applied to obtain more realistic activity durations. Another shortcoming of those methods is the lack of control over the consumption of buffers (Zohrehvandi et al., 2020). In this research, buffer consumption is controlled by using a dynamic method. Due to varying circumstances in different phases of the project in terms of the duration of each phase, the amounts of activities’ resources, and the complexity of the activities network, it is essential that buffer consumption be controlled dynamically. In this way, the number of Academia Letters, January 2022 ©2022 by the author — Open Access — Distributed under CC BY 4.0 Corresponding Author: Shakib Zohrehvandi, shakibzohrevandi@gmail.com Citation: Zohrehvandi, S. (2022). Modeling in project planning & scheduling in construction management and project time optimization. Academia Letters, Article 4765. https://doi.org/10.20935/AL4765. 2 buffers that remain unconsumed in each phase of the project will be transferred to the next phase. In addition, Zohrehvandi et al. (2021) proposed a project time optimization algorithm for calculating project buffer and feeding buffers as well as dynamic controlling of buffer consumption in different phases of a wind power plant project for finding a more realistic project duration. The author is currently working deeply on this topic and has several articles under review that will develop this topic. Zohrehvandi et al. (2019) introduced a reconfigurable model that is a combination of a schedule model and a queuing system M/M/m/K to reduce the duration of the wind turbine construction project closure phase and reduce the project documentation waiting time in the queue. Also, Zohrehvandi et al. (2017) presented an algorithm for sequencing and scheduling of the activities in the project completion phase and reduced the duration of the phase. Recently, Zohrehvandi and Soltani (2022) discussed the state of the art on models and methods for project buffer management and time optimization of construction projects and manufacturing industries. This research investigated the literature from modeling and optimization in project planning & scheduling in construction management and project time optimization. According to the investigation, research carried out so far in the field of project buffer management and time optimization generally concentrated on traditional buffer management methods. Although in some cases, scheduling methods have been employed to manage the buffer of a project, most researchers have used traditional methods of buffer management. The focus of this study has been on the introduction and application of hybrid algorithms and models of simultaneous Buffer sizing and Buffer consumption. Academia Letters, January 2022 ©2022 by the author — Open Access — Distributed under CC BY 4.0 Corresponding Author: Shakib Zohrehvandi, shakibzohrevandi@gmail.com Citation: Zohrehvandi, S. (2022). Modeling in project planning & scheduling in construction management and project time optimization. Academia Letters, Article 4765. https://doi.org/10.20935/AL4765. 3 References Blackstone, J.H., Cox, J.F., and Schleier, J.G., 2009. A tutorial on project management from a theory of constraints perspective. International Journal of Production Research, 47 (24), 7029–7046, https://doi.org/10.1080/00207540802392551. E.M. Goldratt, Critical Chain, North River Press, New York, 1997 Goldratt, E. M., & Cox, J. 1984. The goal: excellence in manufacturing. North River Press. Herroelen, W., & Leus, R. (2001). On the merits and pitfalls of critical chain scheduling. Journal of operations management, 19(5), 559-577, https://doi.org/10.1016/S02726963(01)00054-7. 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Zohrehvandi, S., Vanhoucke, M. and Khalilzadeh, M. (2020), “A project buffer and resource management model in energy sector; a case study in construction of a wind farm project”, Academia Letters, January 2022 ©2022 by the author — Open Access — Distributed under CC BY 4.0 Corresponding Author: Shakib Zohrehvandi, shakibzohrevandi@gmail.com Citation: Zohrehvandi, S. (2022). Modeling in project planning & scheduling in construction management and project time optimization. Academia Letters, Article 4765. https://doi.org/10.20935/AL4765. 5 International Journal of Energy Sector Management, Vol. 14 No. 6, pp. 1123-1142. https://doi.org/10.1108/IJESM-10-2019-0025. Academia Letters, January 2022 ©2022 by the author — Open Access — Distributed under CC BY 4.0 Corresponding Author: Shakib Zohrehvandi, shakibzohrevandi@gmail.com Citation: Zohrehvandi, S. (2022). Modeling in project planning & scheduling in construction management and project time optimization. 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