E-Commerce Logistics Software Package Tracking and Route Planning and Optimization System of Embedded Technology Based on the Intelligent Era

IF 1.1 4区计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

IET Computers and Digital Techniques Pub Date : 2024-10-11 DOI:10.1049/2024/6687853

Dan Zhang, Zhiyang Jia

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Abstract

In the Internet era, the e-commerce industry has risen, its development scale continues to expand, cross-border e-commerce (CBEC) has also been born, and it is now in the stage of sustainable development. The rapid development of CBEC also needs the strong support of logistics, the two are inseparable, and today, the development scale of CBEC is constantly expanding. The existing e-commerce logistics (ECL) model is also gradually unable to meet the increasingly diverse needs of users, and new logistics models need to be actively explored. To change this situation, this paper carried out a specific analysis of CBEC logistics model, and applied embedded technology to ECL, which also built a logistics tracking system. At the same time, combined with the ant colony algorithm, the paper carried out experimental research on the logistics package distribution route planning problem. From the experimental results, in terms of average delivery time, the algorithm’s result was 25.95 hr, while the traditional algorithm was 32.53 hr; in terms of average distribution freight cost, the algorithm’s result was 163.3 yuan, while the traditional algorithm was 257.7 yuan; in terms of average distribution cost, this algorithm’s result was 131.53 yuan, while the traditional algorithm was 211.68 yuan. To sum up, this algorithm could effectively optimize the distribution route of logistics packages and improve the efficiency of package transportation.

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基于智能时代嵌入式技术的电子商务物流软件包跟踪与路线规划优化系统

在互联网时代，电子商务产业异军突起，发展规模不断扩大，跨境电子商务（CBEC）也应运而生，目前正处于可持续发展阶段。CBEC 的快速发展也需要物流的大力支持，二者密不可分，如今，CBEC 的发展规模正在不断扩大。现有的电子商务物流（ECL）模式也逐渐无法满足用户日益多样化的需求，需要积极探索新的物流模式。为了改变这一现状，本文对 CBEC 物流模式进行了具体分析，并将嵌入式技术应用到 ECL 中，还构建了物流跟踪系统。同时，结合蚁群算法，本文对物流包裹配送路线规划问题进行了实验研究。从实验结果来看，在平均配送时间方面，该算法的结果为25.95小时，而传统算法为32.53小时；在平均配送运费方面，该算法的结果为163.3元，而传统算法为257.7元；在平均配送成本方面，该算法的结果为131.53元，而传统算法为211.68元。综上所述，该算法可以有效优化物流包裹的配送路线，提高包裹运输效率。

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来源期刊

IET Computers and Digital Techniques 工程技术-计算机：理论方法

CiteScore

3.50

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： IET Computers & Digital Techniques publishes technical papers describing recent research and development work in all aspects of digital system-on-chip design and test of electronic and embedded systems, including the development of design automation tools (methodologies, algorithms and architectures). Papers based on the problems associated with the scaling down of CMOS technology are particularly welcome. It is aimed at researchers, engineers and educators in the fields of computer and digital systems design and test. The key subject areas of interest are: Design Methods and Tools: CAD/EDA tools, hardware description languages, high-level and architectural synthesis, hardware/software co-design, platform-based design, 3D stacking and circuit design, system on-chip architectures and IP cores, embedded systems, logic synthesis, low-power design and power optimisation. Simulation, Test and Validation: electrical and timing simulation, simulation based verification, hardware/software co-simulation and validation, mixed-domain technology modelling and simulation, post-silicon validation, power analysis and estimation, interconnect modelling and signal integrity analysis, hardware trust and security, design-for-testability, embedded core testing, system-on-chip testing, on-line testing, automatic test generation and delay testing, low-power testing, reliability, fault modelling and fault tolerance. Processor and System Architectures: many-core systems, general-purpose and application specific processors, computational arithmetic for DSP applications, arithmetic and logic units, cache memories, memory management, co-processors and accelerators, systems and networks on chip, embedded cores, platforms, multiprocessors, distributed systems, communication protocols and low-power issues. Configurable Computing: embedded cores, FPGAs, rapid prototyping, adaptive computing, evolvable and statically and dynamically reconfigurable and reprogrammable systems, reconfigurable hardware. Design for variability, power and aging: design methods for variability, power and aging aware design, memories, FPGAs, IP components, 3D stacking, energy harvesting. Case Studies: emerging applications, applications in industrial designs, and design frameworks.