Multi-AGV Scheduling under Limited Buffer Capacity and Battery Charging Using Simulation Techniques

In recent years, automated guided vehicles (AGVs) have been widely adopted to automate material handling procedures in manufacturing shopfloors and distribution centers. AGV scheduling is the procedure of allocating a transportation task to an AGV, which has large impacts on the efficiency of an AGV...

Full description

Saved in:
Bibliographic Details
Published inApplied sciences Vol. 14; no. 3; p. 1197
Main Authors Park, Jin-Sung, Kim, Jun-Woo
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.01.2024
Subjects
AGV scheduling
automated guided vehicles (AGVs)
Automatic guided vehicles
Automation
Battery chargers
Energy consumption
Energy efficiency
Flexibility
FlexSim software
Genetic algorithms
Industrial equipment and supplies industry
Integer programming
Linear programming
Manufacturing
material handling automation
Materials handling
Methods
Operations management
Optimization techniques
Scheduling
Simulation
Simulation methods
Work in process
Online AccessGet full text

Cover

More Information
Summary:In recent years, automated guided vehicles (AGVs) have been widely adopted to automate material handling procedures in manufacturing shopfloors and distribution centers. AGV scheduling is the procedure of allocating a transportation task to an AGV, which has large impacts on the efficiency of an AGV system with multiple AGVs. In order to optimize the operations of multi-AGV systems, AGV scheduling decisions should be made with consideration of practical issues such as buffer space limitations and battery charging. However, previous studies have often overlooked those issues. To fill this gap, this paper proposes a simulation-based multi-AGV scheduling procedure for practical shopfloors with limited buffer capacity and battery charging. Furthermore, we propose three kinds of rules: job selection rules, AGV selection rules, and charging station selection rules, for AGV scheduling in practical shopfloors. The performance of the rules is evaluated through multi-scenario simulation experiments. The FlexSim software v.2022 is used to develop a simulation model for the experiments, and the experimental findings indicate that the job selection rules have larger impacts on the average waiting time than the other kinds of rules.
ISSN:2076-3417
2076-3417
DOI:10.3390/app14031197