TY - JOUR
T1 - Precast production scheduling in off-site construction: Mainstream contents and optimization perspective
AU - Wang, Liang
AU - Zhao, Yueqiao
AU - Yin, Xianfei
N1 - Funding Information:
The GA was found to offer better optimization effects in ensuring on-time delivery as well as in optimizing resource allocation problems; therefore, it has been extensively applied in PPS optimization research in the context of OSC (Li and Love, 1998). Chan and Hu (2001) compared the optimization performance of GA, rapid access (RA), and Gupta, Palmer, Campbell-Dudek-Smith (CDS) algorithms on the flow shop scheduling problem, and the results showed that the optimization performance of the GA was more reliable and stable for generating a set of near-optimal solutions. The GA is also an efficient way to solve scheduling problems in situations with more realistic constraints and complex production environments. For example, Leu and Hwang (2002) demonstrated the flexibility and efficiency of the GA in addressing the PC flow shop scheduling problem by considering resource constraints and mixed production strategies. Ko and Wang (2010) developed a GA-based decision support system to obtain an appropriate PPS scheme. As shown in these examples, GA has demonstrated excellent performance in finding the optimal solution to a problem; thus, such a system could assist decision-makers in devising better production plans.This research was funded by the Humanities and Social Sciences Youth Foundation of Ministry of Education of China (No. 22YJCZH172). The work described in this paper was also supported by the National Social Science Fund of China (No. 18ZDA043), the National Natural Science Foundation of China (NSFC) (NOs. 71974047, 71901077), the Natural Science Foundation of Liaoning Province (No. 2021-BS-072), and the Fundamental Research Funds of the Educational Department of Liaoning Province for the Colleges and Universities (No. LJKQR2021003).
Funding Information:
This research was funded by the Humanities and Social Sciences Youth Foundation of Ministry of Education of China (No. 22YJCZH172 ). The work described in this paper was also supported by the National Social Science Fund of China (No. 18ZDA043 ), the National Natural Science Foundation of China ( NSFC ) (NOs. 71974047 , 71901077 ), the Natural Science Foundation of Liaoning Province (No. 2021-BS-072 ), and the Fundamental Research Funds of the Educational Department of Liaoning Province for the Colleges and Universities (No. LJKQR2021003 ).
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/6/15
Y1 - 2023/6/15
N2 - Precast production scheduling (PPS) is a key factor that enables efficient off-site construction (OSC) and has received considerable attention from researchers. However, there is still a lack of systematic analysis and summary of existing PPS-related studies in the OSC domain to identify current research gaps and predict future research directions. Thus, 75 relevant academic publications were selected for this systematic review. The current research status of PPS was analyzed from four aspects (flow shop scheduling, production rescheduling, internal resource constraints, and external supply chain constraints) to explore the mainstream contents and optimization perspectives of PPS research. The research findings showed that (1) research on flow shop scheduling of precast components (PCs) was dominant in the PPS domain, and the genetic algorithm (GA) was the most applied optimization algorithm; (2) worker allocation strategy, mold grouping, and layout planning of production space were the main starting points for optimizing PPS from a resource perspective; and (3) establishing a collaborative scheduling mechanism by integrating various departments of the OSC supply chain to achieve the just-in-time (JIT) delivery strategy was the main idea for optimizing PPS from the supply chain perspective. This study revealed potential future research focuses in the field of PPS, including PC flow shop scheduling based on carbon emission targets, distributed permutation flow shop scheduling of PCs, layout optimization for intelligent production shops, and production scheduling mechanisms based on digital technology. This study provides theoretical guidance to promote the future development of PPS research in the field of OSC and can help precast production practitioners manage production scientifically and efficiently.
AB - Precast production scheduling (PPS) is a key factor that enables efficient off-site construction (OSC) and has received considerable attention from researchers. However, there is still a lack of systematic analysis and summary of existing PPS-related studies in the OSC domain to identify current research gaps and predict future research directions. Thus, 75 relevant academic publications were selected for this systematic review. The current research status of PPS was analyzed from four aspects (flow shop scheduling, production rescheduling, internal resource constraints, and external supply chain constraints) to explore the mainstream contents and optimization perspectives of PPS research. The research findings showed that (1) research on flow shop scheduling of precast components (PCs) was dominant in the PPS domain, and the genetic algorithm (GA) was the most applied optimization algorithm; (2) worker allocation strategy, mold grouping, and layout planning of production space were the main starting points for optimizing PPS from a resource perspective; and (3) establishing a collaborative scheduling mechanism by integrating various departments of the OSC supply chain to achieve the just-in-time (JIT) delivery strategy was the main idea for optimizing PPS from the supply chain perspective. This study revealed potential future research focuses in the field of PPS, including PC flow shop scheduling based on carbon emission targets, distributed permutation flow shop scheduling of PCs, layout optimization for intelligent production shops, and production scheduling mechanisms based on digital technology. This study provides theoretical guidance to promote the future development of PPS research in the field of OSC and can help precast production practitioners manage production scientifically and efficiently.
KW - 2023 OA procedure
U2 - 10.1016/j.jclepro.2023.137054
DO - 10.1016/j.jclepro.2023.137054
M3 - Review article
SN - 0959-6526
VL - 405
JO - Journal of cleaner production
JF - Journal of cleaner production
M1 - 137054
ER -