.png){kind=icon}
返回
Iot-enabled path optimization for smart logistics using Ant Colony Algorithm
.png){kind=icon}
PRE
AI
DOI：10.1007/s13198-025-03039-1.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The logistics sector faces persistent challenges in efficient and reliable route planning, particularly in fast-changing, data-intensive environments. To address these, we propose an IoT-enabled logistics framework built on a layered fog-cloud architecture for real-time data acquisition, processing, and decision-making. Leveraging an optimized Ant Colony Algorithm (ACA), the system identifies the most efficient transportation routes using live operational data. Comparative analysis with traditional optimization methods shows the ACA-based approach consistently reduces delivery delays and improves route selection under diverse operational constraints. By integrating IoT infrastructure with ACA optimization, the framework offers a scalable, adaptive, and data-driven solution that enhances service quality and operational efficiency in modern logistics.
Keyword:
Logistics
Internet of things
Optimization
Ant Colony Algorithm
期刊
I
IF:
1.4
论文数:
370
被引数:
3.0K
机构
引用论文
Energy-Aware Service Function Chain Embedding in Edge-Cloud Environments for IoT Applications面向物联网应用的边缘云环境中的能量感知服务功能链嵌入
PREAI
分享收藏Information System Framework Architecture for Organization Agnostic Logistics Utilizing Standardized IoT Technologies适用于组织无关物流的标准物联网技术应用的信息系统框架架构
OAAI
OAAI分享收藏分享收藏分享收藏Optimization of logistics collaborative distribution routing based on improved Ant Colony Algorithm
PREAI
分享收藏A secure blockchain-oriented data delivery and collection scheme for 5G-enabled IoD environment
PREAI
分享收藏Smart Logistics Path for Cyber-Physical Systems With Internet of Things基于物联网的信息物理系统智能物流路径.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容