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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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Multi-AGV dispatching and routing problem based on a three-stage decomposition method.

Ye Jun Hu¹, Liang Cai Dong¹, Lei Xu¹

¹College of Logistics Engineering, Shanghai Maritime University, Shanghai, 201306, China.

Mathematical Biosciences and Engineering : MBE

|October 30, 2020

Summary

This summary is machine-generated.

This study optimizes automated guided vehicle (AGV) routing in container terminals by minimizing travel distance and response times. A novel three-stage solution combining A* and time windows enhances system efficiency and path planning.

Keywords:

Multi-AGV systems dispatching and routing problem no conflict three-stage decomposition

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Area of Science:

Logistics and Supply Chain Management
Operations Research
Robotics and Automation

Background:

Automated guided vehicles (AGVs) are crucial for horizontal transport in automated container terminals.
The dispatching and routing problem (DRP) for AGVs is a fundamental challenge.
Practical factors like conflict avoidance and path smoothness complicate AGV operations.

Purpose of the Study:

To develop an optimized model for AGV dispatching and routing.
To minimize AGV travel distance, operation time, and response time.
To address real-world constraints such as conflict avoidance and path adjustments.

Main Methods:

A three-stage decomposition solution combining pre-planning and real-time planning algorithms.
Integration of the A* algorithm with the time window principle for path planning.
Sequential path planning for each AGV in a time-ordered manner.

Main Results:

Demonstrated effectiveness in path search and time optimization for AGV systems.
Significant improvement in overall system efficiency shown through comparative analysis.
Successful handling of complex routing scenarios with practical constraints.

Conclusions:

The proposed method effectively solves the AGV dispatching and routing problem.
The hybrid approach enhances AGV path planning and operational efficiency.
This solution is validated for various scales of automated container terminal operations.