Hao Hu

Dr. Hao Hu


Research Focus & Metrics

Academic Career Length

26Years (2001-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2017 in Journal of Computing in Civil Engineering
Verified
Journal Article
Closed access
ZWZhaojing Wang
Zhaojing Wang
HHHao Hu
Hao Hu
Production scheduling plays a key role in the prefabricated construction productivity and on-time delivery of precast components (PCs). However, the processes before and after the production of PCs were ignored in previous scheduling studies. These operations account for a large proportion of the PCs’ processing time in practice. To ensure the accurate calculation of PC’s completion time and its on-time delivery, this study integrates the mold manufacturing, PC storing, and transportation processes to modify the traditional production-scheduling model from the perspective of the whole PC supply chain. Further, the three scenarios of daytime, night, and all-day transportation are analyzed to conform to the practice. Based on the genetic algorithm, two case studies are conducted to test the validity of the proposed scheduling model. The modified schedule could achieve 17.7, 35.7, and 15.4% cost savings in the three scenarios, respectively. The methodology will enhance the feasible production scheduling and promote on-time delivery of PCs.

1 January 2015 in Transportation Research Part E: Logistics and Transportation Review
Verified
Journal Article
Closed access
JJJian Gang Jin
Jian Gang Jin
Lee Der-HorngLee Der-Horng
Lee Der-Horng
HHHao Hu
Hao Hu

1 December 2002 in Journal of Construction Engineering and Management
Verified
Journal Article
Closed access
WCW. T. Chan
W. T. Chan
HHHao Hu
Hao Hu
Current scheduling practices in precast plants are fairly basic and depend greatly on experience. This may lead to inefficient resource utilization, over-inventory, and/or missing delivery dates. Computer assisted scheduling may therefore be useful in producing better production schedules. This paper shows how constraint programming (CP) can be applied in production scheduling for precast plants. The paper describes a constrained precast scheduling model that incorporates the key constraints and objectives considered by production schedulers. A capacity-based backward-scheduling earliest due date rule and a CP approach are developed to solve the model. The CP approach is computationally efficient, even though it incorporates many problem-derived constraints. The efficiency of the CP approach lies in the fact that the representation (model) is separated from the algorithm (solver). Strategies to improve the performance of the CP approach are identified, and the CP approach is compared against commonly used heuristic rules on an example problem.

1 July 2002 in Journal of Computing in Civil Engineering
Verified
Journal Article
Closed access
WCW. T. Chan
W. T. Chan
HHHao Hu
Hao Hu
There are two alternatives for production organization in precast factories—namely, the comprehensive method and the specialized method. Production scheduling under the specialized alternative has been found to be a difficult optimization problem if heterogeneous elements are involved. A flow shop sequencing model that incorporates actual constraints encountered in practice is proposed for this difficult case of precast production scheduling. The model is solved using a genetic algorithm (GA). The traditional minimize makespan and the more practical minimize tardiness penalty objective functions are optimized separately, as well as simultaneously using a normalized weighted GA. Comparisons between the GA and classical heuristic rules show that the GA can obtain good schedules for the model, giving a family of solutions that are at least as good as those produced by the use of heuristic rules.

1 June 2017 in Computer-Aided Civil and Infrastructure Engineering
Verified
Journal Article
Open access
PDF file
ZWZhaojing Wang
Zhaojing Wang
HHHao Hu
Hao Hu
WZWei Zhou
Wei Zhou
Radio frequency identification (RFID) helps improve supply chain efficiency by providing item-level identification and real-time information. Today, barcode continues to be the main identification technology for precast construction applications. In this research, we investigate the data-driven mechanisms and benefits of utilizing RFID in knowledge-based precast construction supply chains. With computer-aided self-learning capability, we simulate three models for manual-, barcode-, and RFID-enabled precast construction supply chain. The results of 100 precast wall-panel construction in a two-echelon precast construction supply chain reveal that the knowledge-based RFID system could generate 62.0% saving of operational costs, which is 29.0% higher than that of a barcode-based system. As a result, the computer-aided adaptive learning mechanism based on RFID is verifiable to improve the overall operational performance by reducing lead time, operational errors, and costs. Due to the lack of existing literature of data technology utilization in the precast construction industry, our findings in this research could improve the decision making regarding technology selection, as well as help with the operationalization of RFID and transformation to intelligent precast construction management in big data environment.

1 August 2014 in Computer-Aided Civil and Infrastructure Engineering
Verified
Journal Article
Open access
PDF file
WZWei Zhu
Wei Zhu
HHHao Hu
Hao Hu
ZHZhaodong Huang
Zhaodong Huang