Promoting sustainable production and consumption practices in the construction machinery industry is crucial for achieving energy savings and reducing carbon emissions. However, there is a lack of targeted studies addressing the challenge of scaling up leasing and recycling while maximizing economic benefits for enterprises. To fill this gap, this paper presents a lease-oriented closed-loop supply chain model that incorporates a carbon tax policy to investigate the impact of the carbon tax rate and consumer preferences for remanufactured products on the supply chain and introduces a leasing compensation–cost apportioning combined contract to achieve supply chain coordination in the construction machinery sector. The model considers differential selling and leasing prices for new and remanufactured products, as well as the recovery rate, under both centralized and decentralized decision-making approaches. The study explores the interrelationships between various parameters through sensitivity analysis and numerical simulation. The results demonstrate that within a certain range of the cost apportioning proportional coefficient and leasing compensation proportional coefficient, the combined contract can lead the supply chain to achieve Pareto optimality. As the carbon tax rate increases, it was observed that the profits for all parties in the supply chain tend to decrease. However, due to the increased demand for remanufactured products, the product recovery rate improves, resulting in a reduction in total carbon emissions in the closed-loop supply chain of construction machinery. Moreover, the profits of all parties and the total supply chain profits initially decrease and then increase with an increasing preference coefficient for remanufactured products among consumers. By leveraging these factors and adopting effective strategies, such as enhancing consumer recognition of remanufactured products and optimizing pricing and cost allocation, it is indeed possible for the profits of all parties and the total profits in the supply chain to surpass the initial values, even in the face of increasing carbon tax rates. This demonstrates the potential for aligning sustainability objectives with economic benefits in the construction machinery industry.

Ready-mixed-concrete (RMC) is an important green and clean building material which is widely used in modern civil engineering. For the large-scale planar foundations of urban public buildings, huge amounts of RMC need to be continuously delivered to the construction site according to strict time windows, which brings the problem of multi-plants collaborative supply. In this paper, considering transportation capacity, initial setting time, and interrupt pumping time, a collaborative scheduling model for production and transportation of RMC with the objective of minimizing the penalty cost of interruption pumping and vehicle waiting time and fuel consumption cost was established. According to the characteristics of the problem, a double chromosome synchronous evolution genetic algorithm was designed. Finally, the model and algorithm proposed in the paper were verified by data experiments. The computing results showed that in two cases of different scenarios, such as ordinary constructions and emergency constructions, the proposed scheduling model can save 18.6 and 24.8% cost respectively. The scheduling model and algorithm proposed in the paper can be applied directly to improve the operational efficiency of RMC supply chain.

The key issues that have always affected the production yield of the construction industry are delays and cost overruns, especially when dealing with large-scale projects and super-high buildings in which multiple tower cranes with overlapping areas are often deployed because of urgent due date and limited space. The service scheduling of tower cranes, which act as the crucial site equipment for lifting and transporting materials, is one of the main problems not only related to the construction progress and project cost but also affecting equipment health, and it may bring security risks. The current work presents a multi-objective optimization model for a multiple tower cranes service scheduling problem (MCSSP) with overlapping areas while achieving maximum interval time of cross-tasks and minimum makespan. For the solving procedure, NSGA-Ⅱ is employed with double-layer chromosome coding and simultaneous coevolutionary strategy design, which can obtain a satisfactory solution through effectively allocating tasks within overlapping areas to each crane and then prioritizing all the assigned tasks. The makespan was minimized, and stable operation of tower cranes without collision was achieved by maximizing the cross-tasks interval time. A case study of the megaproject Daxing International Airport in China has been conducted to evaluate the proposed model and algorithm. The computational results illustrated the Pareto front and its non-dominant relationship. The Pareto optimal solution outperforms the results of the single objective classical genetic algorithm in terms of overall performance of makespan and interval time of cross-tasks. It also can be seen that significant improvement in the time interval of cross-tasks can be achieved at the cost of a tiny increase in makespan, which means effective avoidance of the tower cranes entering the overlapping area at the same time. This can help eliminate collision, interference and frequent start-up and braking of tower cranes, leading to safe, stable and efficient operation on the construction site.

Construction machinery operations are intrinsically linked to critical societal challenges, including safety risks and carbon emissions. In response to the high incidence of fatal accidents during installation and dismantling phases, the Chinese government has officially promoted integrated installation–dismantling services to enhance construction safety since 2023. However, the economic viability of this policy for leasing companies remains largely underexplored. To address this gap, this paper develops a leasing-oriented closed-loop construction machinery supply chain model that incorporates integrated installation–dismantling services under an industrial internet platform. The study first compares and analyzes the product leasing demand, installation and dismantling demand, and supply chain profits under both centralized and decentralized decision-making scenarios. Based on these analyses, a profit–cost sharing joint contract is designed to coordinate the supply chain. Furthermore, the interrelationships among key parameters are examined through a sensitivity analysis and numerical simulation. The results reveal that enhancing leasing information services increases both the demand for construction machinery and the platform’s operating costs. These costs are positively correlated with the product’s selling price, leading to higher purchasing costs for lessees. Similarly, improving information services for installation and dismantling raises the platform’s operating costs and enhances service levels, which in turn increases installation and dismantling costs for lessees. The findings demonstrate that within a certain range of cost-sharing and leasing-sharing proportional coefficients, the joint contract enables the supply chain to achieve Pareto optimization. This approach simultaneously alleviates economic pressure on lessees, improves construction safety, and promotes the integration of installation and dismantling services.

Leasing and recycling are important methods for developing the low-carbon sustainability of the construction machinery industry. However, there are some dilemmas caused by the extreme limitations of product service life. There has been little research on construction machinery leasing thus far and a lack of description of its unique characteristics in previous models. Focusing on the problem of pricing and coordination, a two-stage model of a leasing closed-loop supply chain based on the practical application of an Industrial Internet platform was proposed. Under centralized and decentralized decision-making scenarios, the prices of leasing and selling, maintenance effort, and recovery rate were calculated, respectively. By using the Shapley value method to optimize the selling price, and the two-part pricing contract to calculate the compensation fee, global profits can be reasonably distributed, while the supply chain can be improved. The effects of different contracts on the improvement of supply chain profit were investigated. Additionally, the correlation among parameters was explored via sensitivity analysis and numerical simulation. The findings show that the maintenance and recycling of construction machinery can be improved by using an Industrial Internet platform while achieving supply chain coordination via contracts. The enhancement of maintenance effort can decrease remanufacturing costs, which are positively correlated with the selling price and leasing price of products, further promoting the recovery rate of used products. The findings of this paper show that manufacturers can take advantage of the Industrial Internet platform to improve recycling efficiency as well as to decrease product prices and remanufacturing costs by promoting remanufacturing technologies. On the other hand, leasers need to enhance the maintenance of construction machinery. Strengthening cooperation via contracts can jointly promote leasing and recycling in the construction machinery industry and help achieve low-carbon sustainable development.

Leasing and recycling are important issues to achieve low-carbon sustainable development of construction machinery industry, however there are some dilemmas bothering which is caused by excessive restriction of product service life. Focusing on the problem of pricing and coordination, a two-stage model of leasing closed-loop supply chain based on the Industrial Internet platform practical application was proposed. Under the centralized and decentralized decision-making scenarios, the price of leasing and selling, maintenance effort and recovery rate are calculated respectively. By using the Shapley value method to optimize the selling price, and the two-part pricing contract to calculate the compensation fee, the global profit is reasonably distributed, while the supply chain achieving Pareto optimality. The performance of different contracts on the improvement of supply chain profit was investigated. And the correlation among parameters was also explored through sensitivity analysis and numerical simulation. The findings showed that maintenance and recycling of construction machinery can be improved with the advantage of the Industrial Internet platform, while achieving the supply chain coordination by contracts. The enhancement of maintenance effort can decrease the remanufacturing cost which is positively correlated to the selling price and leasing price of product, furthermore promoting the recovery rate of used products. In the future, reasonable control of platform cost can help improve the recycling of construction machinery.