Abstract Nowadays, the use of heavy mobile cranes in on-site construction of industrial projects has become inevitable. Due to the high rental cost of such cranes, an optimized plan is essential for the multiple crane lifts. This plan reduces the operating costs of the crane by minimizing waste time and lessens the potential of failures and accidents. However, developing an efficient lift plan can be challenging and time-consuming, considering the large number of lift options. This article presents a novel framework based on an informed search algorithm called A-star, which provides a semi-optimum lift plan based on a predetermined lifting sequence. This system talks to a comprehensive database to provide initial data. The proposed framework is applied successfully and validated in an actual modular construction project in Alberta, Canada. The results show a significant reduction in the total cost compared with the previously used lift planning algorithm.

中文翻译：

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模块化施工中起重机位置和配置半优化的A-Star算法

摘要 如今，重型移动式起重机在工业项目现场施工中的使用已成为必然。由于此类起重机的租赁成本很高，因此对于多台起重机升降机来说，优化计划至关重要。该计划通过最大限度地减少浪费时间和减少故障和事故的可能性来降低起重机的运营成本。然而，考虑到大量的电梯选项，制定有效的电梯计划可能具有挑战性且耗时。本文提出了一种基于称为 A-star 的知情搜索算法的新颖框架，它提供了基于预定提升序列的半最优提升计划。该系统与综合数据库对话以提供初始数据。提议的框架在加拿大艾伯塔省的一个实际模块化建筑项目中得到了成功应用和验证。