Department of Industrial Engineering, School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China.
Math Biosci Eng. 2023 Jan 18;20(3):5993-6015. doi: 10.3934/mbe.2023259.
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.
一直以来，影响建筑行业产量的关键问题是延误和成本超支，尤其是在处理大型项目和超高建筑物时，由于紧迫的截止日期和有限的空间，通常会部署多个重叠区域的塔吊。塔吊作为起重和运输材料的关键现场设备，其服务调度不仅与施工进度和项目成本有关，还会影响设备健康状况，甚至带来安全风险。目前的工作提出了一个具有重叠区域的多塔吊服务调度问题（MCSSP）的多目标优化模型，旨在实现最大交叉任务间隔时间和最小完工时间。对于求解过程，采用 NSGA-Ⅱ 算法，并采用双层染色体编码和同时协同进化策略设计，可以通过有效地在重叠区域内为每个塔吊分配任务，并为所有分配的任务确定优先级，从而获得令人满意的解决方案。通过最大化交叉任务间隔时间来最小化完工时间，并通过最大化交叉任务间隔时间来实现塔吊的稳定运行而不会发生碰撞。对中国大兴国际机场的大型项目进行了案例研究，以评估所提出的模型和算法。计算结果说明了帕累托前沿及其非支配关系。与单目标经典遗传算法的结果相比，所提出的模型和算法在完工时间和交叉任务间隔时间的整体性能方面表现更好。还可以看出，在不增加完工时间的情况下，可以显著提高交叉任务的时间间隔，这意味着可以有效地避免塔吊同时进入重叠区域。这有助于消除塔吊碰撞、干扰和频繁启动和制动，从而实现施工现场的安全、稳定和高效运行。
