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An A-Star algorithm for semi-optimization of crane location and configuration in modular construction

机译:一种半优化起重机定位和模块化构造配置的A-Star算法

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摘要

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.
机译:如今,在现场工业项目的现场建设中使用了重型移动起重机已经变得不可避免。由于这种起重机的租金较高,优化的计划对于多个起重机升降机至关重要。该计划通过最大限度地减少浪费时间来降低起重机的运营成本,减少故障和事故的潜力。然而,考虑到大量提升选项,开发有效的提升计划可能是具有挑战性和耗时的。本文提出了一种基于所通知的搜索算法的新颖框架,称为A-STAR,其提供基于预定提升序列的半最佳升力计划。该系统与全面的数据库交谈以提供初始数据。拟议的框架在加拿大艾伯塔省的实际模块化建设项目中成功应用并验证。与先前使用的提升规划算法相比,结果表明总成本显着降低。

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