研究了带时间窗多车场车辆路径问题(multi-depots vehicle routing problem with time windows,MDVRPTW),建立MDVRPTW模型,设计了结合混合高斯模型(Gaussian mixture model,GMM)聚类算法的自适应大邻域搜索(adaptive large neighborhood...研究了带时间窗多车场车辆路径问题(multi-depots vehicle routing problem with time windows,MDVRPTW),建立MDVRPTW模型,设计了结合混合高斯模型(Gaussian mixture model,GMM)聚类算法的自适应大邻域搜索(adaptive large neighborhood search,ALNS)算法。通过在邻域变换前将客户集进行分类,优化初始解,提高算法运算效率。算法使用6种不同变换因子,采用得分系统对变换因子进行评价,使算法能够在迭代的不同阶段自适应地选择合适的变换因子。分析了参数设置值的合理性,设计了3组仿真实验,实验结果验证了算法的高效性。展开更多
The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
随着通信技术升级以及5G通信应用的驱动,各种智能设备所需的滤波器数量激增,促进了滤波器市场的繁荣,但对其性能要求也越来越高,例如大带宽、高频率、高功率容量、微型化、集成化以及低成本等指标是学术界与产业界重点关注的方向,而基...随着通信技术升级以及5G通信应用的驱动,各种智能设备所需的滤波器数量激增,促进了滤波器市场的繁荣,但对其性能要求也越来越高,例如大带宽、高频率、高功率容量、微型化、集成化以及低成本等指标是学术界与产业界重点关注的方向,而基于薄膜体声波谐振器(Thin Film Bulk Acoustic Resonator,FBAR)技术的FBAR滤波器已成为最有前景的滤波器之一。另外,当前空腔型FBAR滤波器已取得了一定的商业成功,但是仍面临性能不足、工艺复杂、成本略高、技术受限等困境。为此,本文试图从器件理论研究与结构优化、高性能压电材料制备与优化、新型工艺开发及技术融合三方面对FBAR滤波器的相关问题与关键技术进行综述,旨在为该研究领域的学者梳理FBAR滤波器技术进阶与迭代的脉络,以期为未来研究的路径与方向提供若干启发性思考。展开更多
文摘研究了带时间窗多车场车辆路径问题(multi-depots vehicle routing problem with time windows,MDVRPTW),建立MDVRPTW模型,设计了结合混合高斯模型(Gaussian mixture model,GMM)聚类算法的自适应大邻域搜索(adaptive large neighborhood search,ALNS)算法。通过在邻域变换前将客户集进行分类,优化初始解,提高算法运算效率。算法使用6种不同变换因子,采用得分系统对变换因子进行评价,使算法能够在迭代的不同阶段自适应地选择合适的变换因子。分析了参数设置值的合理性,设计了3组仿真实验,实验结果验证了算法的高效性。
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
文摘随着通信技术升级以及5G通信应用的驱动,各种智能设备所需的滤波器数量激增,促进了滤波器市场的繁荣,但对其性能要求也越来越高,例如大带宽、高频率、高功率容量、微型化、集成化以及低成本等指标是学术界与产业界重点关注的方向,而基于薄膜体声波谐振器(Thin Film Bulk Acoustic Resonator,FBAR)技术的FBAR滤波器已成为最有前景的滤波器之一。另外,当前空腔型FBAR滤波器已取得了一定的商业成功,但是仍面临性能不足、工艺复杂、成本略高、技术受限等困境。为此,本文试图从器件理论研究与结构优化、高性能压电材料制备与优化、新型工艺开发及技术融合三方面对FBAR滤波器的相关问题与关键技术进行综述,旨在为该研究领域的学者梳理FBAR滤波器技术进阶与迭代的脉络,以期为未来研究的路径与方向提供若干启发性思考。
