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CPU-GPU solution for bus-based freight scheduling under uncertainty
DOI:10.1016/j.tre.2025.104508.png)
摘要
En 中文
• 提出了一种CPU-GPU异构架构用于算法实现。
• 针对基于公交的货运调度,构建了一个两阶段随机规划模型。
• 在算法中嵌入了GPU加速的自适应大邻域搜索。
• CPU-GPU架构将计算时间从小时级缩短至分钟级甚至秒级。
• 进行了敏感性分析,为设计稳健的货运调度计划提供洞见。
Keyword:
Bus-based freight transportation
CPU-GPU heterogeneous architecture
GPU acceleration
Stochastic programming
Metaheuristic algorithm
期刊
T
IF:
0
论文数:
247
被引数:
0
机构
引用论文
Qiao W, Créput J (2020) Multiple k-opt evaluation multiple k-opt moves with GPU high performance local search to large-scale traveling salesman problems. Annals of Mathematics and Artificial Intelligence 88(4): 347–365.乔 W, Créput J (2020) 多 k-opt 评估:使用 GPU 高性能局部搜索进行大规模旅行商问题的多 k-opt 移动。数学与人工智能年刊 88(4): 347–365.
Wang X, Zhen L, Wang S (2024b) Optimizing an express delivery mode based on high-speed railway and crowd-couriers. Transport Policy 159: 157–177.王X, Zhen L, 王S (2024b) 基于高速铁路和众包快递员的快递配送模式优化。Transport Policy 159: 157–177.
An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows带时间窗的取货和送货问题的自适应大邻域搜索启发式
Integrated people-and-goods transportation systems: from a literature review to a general framework for future research
TRANSPORT REVIEWS
IF9.9
Research on the Optimization of Urban-Rural Passenger and Postal Integration Operation Scheduling Based on Uncertainty Theory
SUSTAINABILITY
IF3.3

