A Review of Production Scheduling for Prefabricated Building Components ()
1. Introduction
The traditional construction industry is based on the site, mainly relying on traditional manpower and experience to build, its production scheduling is often time-consuming and laborious, and easily confused, so the construction efficiency is extremely low (Xu et al., 2020) . In addition, with the gradual disappearance of China’s demographic dividend, the cost of labor is also gradually increasing, which correspondingly leads to an increase in production scheduling costs (Jiang & Wu, 2021) . With the development of prefabricated building, the construction industry has undergone a sea change, the production method from the site moved to the factory, as in the manufacturing industry, the production efficiency has been well controlled. However, with the rapid development of high technology, people are no longer satisfied with the existing production efficiency, and it has been found that the production and construction process, such as the allocation of resources, coordination of personnel matters, and adapt to fluctuating market demand and other issues on the production scheduling challenges, so it is important to further optimize the production scheduling of the prefabricated building (Yuan et al., 2021b) .
At present, the research on production scheduling at home and abroad is relatively mature, but the research on component production scheduling for prefabricated buildings is still relatively limited (Bataglin et al., 2020) . This paper uses the VOS viewer analysis tool to measure and visualize the literature on production scheduling in the past ten years, summarizes the research hotspots and development trends of production scheduling for prefabricated buildings in recent years and provides insights into techniques and methods to optimize the production scheduling problems in recent years, and discusses the main research directions for the future development of prefabricated buildings. It also summarizes the research hotspots and trends in production scheduling in recent years, and provides insights into the techniques and methods that can optimize the production scheduling problems in recent years, and discusses the main research directions for the future development of prefabricated buildings.
2. Related Work
In this paper, through a combination of quantitative and qualitative methods, it reads and organizes the classical literature on production scheduling through VOS viewer, and at the same time, this paper use SCOPUS database for keyword search, and focus on 1470 classical literatures in the fields of engineering and technology, management, and operations research, etc., and finally, through systematic screening, we select 212 literatures as the basic data of this paper, and launch the subsequent quantitative analysis.
Based on the above data to conduct a high-frequency co-citation literature study on production scheduling issues, the network visualization mapping was performed by VOS viewer tool, and the results are shown in Figure 1. Subsequently, the visual mapping of Figure 1 was counted into tabular data, analyzed for the top 10 keywords with high citation frequency, and organized as shown in Table 1. Combined with the trend graphs in the VOS viewer tool in the past ten years, it can be summarized that the hotspots of production scheduling are mainly
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Figure 1. Co-occurrence analysis of production scheduling keywords.
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Table 1. High-frequency keywords for production scheduling research.
classified into three categories: optimization algorithms, scheduling models, and production environment factors. First of all, the optimization algorithm is the use of various advanced technologies and scientific means (such as artificial intelligence technology) to update the optimization of mathematical algorithms in recent years, so as to promote the evolution of various types of scheduling models and the establishment of new, and the establishment of the scheduling model in the establishment of the process of the various types of factors of production, so these three categories is the hot spot of the current research (Guo & Zhang, 2022) . In addition, it is found that the development of production scheduling tends more and more to the study of complex problems, especially for the study of mass production problems in variable environments and multi-objective constraints, and researchers are paying more and more attention to the diversity and complexity of production scheduling of prefabricated components for prefabricated buildings (Zaalouk et al., 2023) .
3. Review of Literature Related to Precast Production Scheduling
The main approaches adopted by domestic and foreign scholars to these hotspot problems are summarized for the three hotspot classifications mentioned above: optimization algorithms, scheduling models and production environment factors.
First of all, optimization algorithms, traditional algorithms including genetic algorithms, simulated annealing algorithms, particle swarm algorithms, ant colony algorithms, and fish swarm algorithms, etc., which have been used in a variety of production scheduling improvement process (Liu et al., 2023) , but with the advancement of science and technology, especially with the birth of artificial intelligence, the use of intelligent optimization algorithms to promote and optimize the process of production scheduling has become dominant. At present, there are more and more means of designing algorithmic optimization using artificial intelligence techniques such as machine learning, deep learning and big data, and intelligent optimization algorithms are widely used in solving a variety of practical engineering problems due to their fast solution speed and high accuracy, which can solve many scheduling problems (Chen & Liu, 2023) .
Secondly, regarding the scheduling model, the production scheduling model established based on various intelligent optimization algorithms can better solve the complex multi-objective practical engineering problems, and the use of visual 3D simulation technology to simulate the whole process of production scheduling, which can better establish and optimize the scheduling model, so as to make the production scheduling problems better solved (Wang et al., 2018a) . Here we must mention the BIM technology which has been widely used in recent years, because BIM technology can make all the major parties involved in the whole life cycle of the project work together and communicate on a unified platform, so it provides more convenient channels for production scheduling, and makes the production scheduling become more efficient (Peiris et al., 2023) .
Aspects of production environmental factors, that is, the environmental conditions of production and other uncertain factors. The production scheduling of prefabricated buildings involves many aspects of engineering project management, which is a relatively complex process that involves a very large number of uncertainties, or a variety of interfering factors, and therefore should be controlled through a series of methods or technical means (Wang et al., 2023) . Usually in the consideration of the production environment factors are mainly studied in terms of normal working hours, abnormal working hours, overtime; production phase of the preemptive and non-preemptive situation; maintenance of parallel processing capacity; the priority of the production of components; the size of the buffer zone between the production station; the combination and size of the staff, the number of resources, the mixed production strategy, the size of the project; the tooling cost, the cost of labor and inventory costs, and so on. Costs of tooling, labor, and inventory, etc. These influences are diverse, complex and uncertain (Chen & Liu, 2023; Guo & Zhang, 2022) .
In summary, during the prefabricated building production scheduling, managers need to fully collaborate with various departments and links, carry out careful planning and effective control, and ultimately achieve the purpose of simplifying the process, reducing costs, reducing waste, saving time and other effective management (Wang et al., 2018b) .
4. Synthesis and Analysis
Aiming at the hot issues on production scheduling in recent years, especially on optimization algorithms, this paper carries out further in-depth research, and summarizes its Key Focus, Advantage, Limitation, and Methodology through a systematic review of more than forty typical articles, as shown in Table 2.
As can be seen from Table 2, the prefabricated components production scheduling problem has been studied in related literature from different perspectives and approaches. Through the above analysis and summary, the study found that some challenges in production scheduling are currently solved using a variety of advanced technologies and optimization algorithms (Yuan et al., 2021a) , which are often integrated forms of combining a variety of technologies and algorithms to promote the optimization of production scheduling of prefabricated building components through a variety of combinations and collaborations to improve the production efficiency (Wang & Liu, 2023) , reduce the cost, and promote the development of prefabricated buildings (Chang et al., 2022) .
1) BIM technology and genetic algorithm integration: first of all, genetic algorithm is an important and very common optimization algorithm in the process of production scheduling improvement (Du et al., 2020) , it can improve production efficiency, reduce costs, etc., but with the development of BIM technology, the use of dynamic simulation as well as multidepartmental collaborative work can greatly enhance the original single use of genetic algorithm model efficiency, and further enhance the accuracy of production scheduling (Yuan et al., 2021a) .
2) Lean Planning Method Enhanced Biogeography Optimization Algorithm: Lean planning method can achieve real-time adjustment and planning in specific scenarios (Xie et al., 2021) , and at the same time enhance biogeography optimization algorithm to promote the optimization and enhancement of production scheduling to help component manufacturers to carry out real-time simulation and planning (Chen et al., 2020) , but this method has certain limitations, and it is not suitable for all scenarios (Yuan et al., 2020) .
3) Dynamic scheduling model management under the multi-objective optimization (MOO) method: firstly, for the complex and changeable production
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Table 2. Research on production scheduling problems of prefabricated building components.
scheduling actual situation (Zhai et al., 2019) , the method of multi-objective optimization is adopted, and dynamic simulation means are implemented to dynamically control the complex and changeable objectives (Yuan et al., 2021b) , so that the simulation tends to be more close to the real scenario, so that the production scheduling can be more rigorous, and the cost can be saved (Yuan et al., 2021a) .
4) Multiple algorithms integration optimization: For each stage of production scheduling to optimize one by one, that is, the use of genetic algorithms, mixed integer linear programming, differential evolution and other advanced algorithms for system integration (Li et al., 2019a) , for the optimal allocation of resources, for different algorithms for different projects to support in-depth analysis and comparison of strategies (Yu, 2021) , so as to carry out effective comparison of the application (Li et al., 2019b) .
On the prefabricated components production scheduling problem is complex and variable (Li et al., 2019b) , its optimization algorithm has a diversity, in the face of a variety of complex project requirements and environmental constraints should be targeted to put forward the corresponding solutions, and is to consider the problem with dynamic thinking, in the face of constantly changing algorithms and technology, to change should change, and constantly evolve to change the mindset of the optimization of production scheduling (Yu et al., 2022) .
5. Future Research Directions for Precast Production Scheduling
With the rapid development of AI technology, production scheduling optimization for prefabricated buildings will add a new boost (Huang et al., 2022) . Future production scheduling optimization will be the integration of a variety of optimization algorithms (genetic algorithm, mixed integer linear programming, differential evolution, etc.), and combined with BIM technology and lean planning methods, the use of AI and machine learning and other advanced technologies, through the use of practical application scenarios to validate the effectiveness of the different production scheduling optimization methods to improve the efficiency of the actual project production, so that the theory and practice can be fully integrated and effectively Fusion of various optimization techniques and methods. Of course, the future of production scheduling optimization must be based on the basis of sustainable development, in the full use of a variety of technical methods, to make full use of resources, reduce carbon emissions to reduce waste, etc., to truly realize the purpose of the green sustainable building (Yuan et al., 2020) .
6. Conclusion
This paper conducts bibliometric and visualization analysis of production scheduling literature in Scopus database by using VOS viewer analysis software, and deeply study the current status of a series of methods and optimization techniques that have been developed and adopted in recent years in the area of production scheduling for prefabricated buildings, and summarize that hotspots of production scheduling are mainly classified into three categories: optimization algorithms, scheduling models, and factors of the production environment (Song et al., 2023) . This paper examines the general trends in production scheduling for prefabricated buildings over the past decade and provides insights into the technologies and methods that have been able to optimize the production scheduling problem in recent years. In the future, with the integration and consolidation of emerging technologies such as BIM technology, AI and machine learning, it will lead to the continuous optimization of production scheduling, with better cost, efficiency, waste reduction, adjustment adaptability, and sustainability, and will further contribute to the continuous development of the entire construction industry (Ruan & Xu, 2022) .
Acknowledgements
This paper was supported by Hainan Provincial Natural Science Foundation of China (621QN0906).
NOTES
*Co author.