基于种群熵动态权重PSO的公铁联运装载单元模数尺寸优化研究  

Module Size Optimization of Loading Units in Highway-Railway Combined Transport Based on Population Entropy Dynamic Weighted PSO

作　　者：陈炼 王义旭 赵南希 王馨梓 CHEN Lian;WANG Yixu;ZHAO Nanxi;WANG Xinzi(Research Institute of Highway,Ministry of Transport,Beijing 100088,China)

机构地区：[1]交通运输部公路科学研究院,北京100088

出　　处：《铁道运输与经济》2024年第11期150-156,共7页Railway Transport and Economy

基　　金：交通运输部公路科学所(院)交通强国试点项目(QG2021-4-17-1)。

摘　　要：集装箱具有保护能力强、结构强度高等优势,其在公铁联运领域的应用越来越普遍。然而,集装箱式载运单元在换装过程中也存在空间利用率低的行业痛点问题。因此,针对常见集装箱式载运单元开展模数尺寸优化研究具有重要实践价值。为此,以提高几类通用公铁联运集装箱的空间利用率为目标,针对组合式装载单元提出了基于种群熵动态权重PSO(EWPSO)的模数尺寸优化设计方法。首先,对装载单元的装箱过程进行建模并考虑额定载重、隔振间隙等约束条件,从而建立以集装箱损失体积最小为目标的适应度优化函数;然后,为避免搜索无效区域,将传统PSO算法中的固定解空间改进为基于种群信息熵的具有实时调整大小功能的动态解空间;接下来,利用基于指数衰减的动态权重参数解决搜索速度和求解精度之间的矛盾。最后通过载运单元模数尺寸参数优化实例验证了所提EWPSO算法在计算时间和全局搜索能力2个方面的优越性。Containers have the advantages of strong protection ability and high structural strength,and they are increasingly applied in the field of highway-railway combined transport.However,there are also industry pain points such as low space utilization during the replacement process of containerized loading units.Therefore,conducting research on module size optimization for common containerized loading units has important practical value.To improve the space utilization of several types of general containers for highway-railway combined transport,this paper proposed a module size optimization design method based on population entropy dynamic weight PSO(EWPSO)for combined loading units.Firstly,the paper modeled the loading process of the loading unit and considered constraints such as rated load and isolation clearance,so as to establish a fitness optimization function with the objective of minimizing container loss volume.Then,to avoid searching for invalid areas,the fixed solution space in the traditional PSO algorithm was improved to a dynamic solution space based on population information entropy with a real-time resizing function.Next,the contradiction between search speed and solution accuracy was resolved by using dynamic weight parameters based on exponential decay.Finally,the superiority of the proposed EWPSO algorithm in terms of computation time and global search capability was verified through an example of optimizing the module size parameters of the loading unit.

关 键 词：公铁联运 装载单元 PSO 信息熵 模数尺寸 

分 类 号：U294.2[交通运输工程—交通运输规划与管理]