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水力发电学报 ›› 2024, Vol. 43 ›› Issue (4): 112-124.doi: 10.11660/slfdxb.20240410

• • 上一篇    

基于E-WOA与AnyLogic耦合的土石方调配机械配置优化

  

  • 出版日期:2024-04-25 发布日期:2024-04-25

Equipment selection optimization of earthwork allocation operation based on E-WOA coupling with AnyLogic

  • Online:2024-04-25 Published:2024-04-25

摘要: 机械配置是土石方调配工程的核心,合理的机械配置是工程施工成本、进度和质量的有效保障。为了精确、高效地寻求出最优的机械配置方案,提出了增强型鲸鱼算法(E-WOA)与AnyLogic耦合的土石方调配机械配置优化方法。首先,通过系统分析土石方调配流程,建立总费用最小的优化模型;其次,采用AnyLogic仿真平台构建了基于多智能体的仿真模型,全面描述设备(挖掘机、自卸汽车、推土机、碾压机)、道路、平台(卸料平台、停车平台)等实体元素之间的交互关系和动态过程;最后,引入收敛速度快、全局性强的E-WOA算法与AnyLogic进行耦合,开发仿真控制器实现耦合模型对优化问题的求解,并结合工程实例进行了分析。结果表明该方法可以节省11.11%的时间和27.34%的费用,为土石方调配工程施工管理决策提供借鉴。

关键词: 土石方调配, 机械配置优化, 仿真模型, 增强型鲸鱼算法, AnyLogic

Abstract: Equipment selection is the core of earthwork allocation engineering, and reasonable equipment selection serves as an effective safeguard for construction cost, progress and quality of a project. This paper describes an enhanced whale optimization algorithm (E-WOA) coupled with AnyLogic simulation platform for optimizing the machinery configuration scheme efficiently. First, an optimization model with the minimum total cost and expense is developed by analyzing the earthwork allocation deployment process systematically. Then, an AnyLogic simulation platform is used to construct a simulation model based on multiple-agents, which comprehensively describes the interaction relationship and dynamic process between equipment (excavator, dump truck, bulldozer, and roller), road, platform (unloading platform and parking platform), and other entity elements. Finally, E-WOA is introduced to couple with AnyLogic, and a simulation controller is developed to control the coupled model for automatic solving of the optimization problem. Application to engineering case studies demonstrates that this method can lead to a time saving of 11.11% and a cost reduction of 27.34%, thereby offering valuable insights for the management of earthwork allocation deployment projects.

Key words: earthwork allocation, equipment selection optimization, simulation model, enhanced whale optimization algorithm (E-WOA), AnyLogic

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