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Logistics Distribution Path Optimization Algorithm Based on Intelligent Management System
1School of Business, Jilin Business and Technology College, Changchun 130507, Jilin, China.
Computational Intelligence and Neuroscience
|October 6, 2022
Summary
This study optimizes logistics distribution paths using radio-frequency identification (RFID) and ant colony algorithms. Results show high positioning accuracy and efficient shortest path identification, reducing costs and errors.
Area of Science:
- Operations Research
- Logistics Management
- Computer Science
Background:
- Logistics distribution involves optimizing vehicles, goods quantity, and paths for efficiency.
- Current distribution methods face challenges in reducing errors, time, and labor costs.
Purpose of the Study:
- To optimize logistics distribution paths for efficient and safe delivery.
- To identify the shortest distribution routes and reduce operational expenses.
Main Methods:
- Utilized radio-frequency identification (RFID) technology for accurate positioning.
- Applied the ant colony algorithm to determine optimal distribution routes.
Main Results:
- RFID systems achieved near 100% positioning accuracy with approximately 300 fixed points.
- The ant colony algorithm accurately identified shortest paths, with a minimal deviation of about 200 meters.
Conclusions:
- Integrated RFID and ant colony algorithms enable intelligent management of logistics distribution.
- The proposed methods significantly enhance the safety, efficiency, and cost-effectiveness of logistics operations.
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