Journal
IEEE ACCESS
Volume 9, Issue -, Pages 33522-33531Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3061288
Keywords
Machine tools; Conferences; Production; Transportation; Task analysis; Heuristic algorithms; Path planning; Automated guided vehicle; improved particle swarm optimization algorithm; scheduling optimization; routing plan
Categories
Funding
- National Natural Science Foundation of China [61773192, 61803192]
- Special fund plan for local science and technology development lead by central authority, Research project of Liaocheng University [318011922]
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This paper studies the AGV path planning problem in smart manufacturing workshops, establishes a mathematical model and proposes an improved particle swarm optimization algorithm to obtain an optimal path. Experimental results show that the algorithm can improve the efficiency of AGV in material transportation.
In smart manufacturing workshops, automated guided vehicles (AGVs) are increasingly used to transport materials required for machine tools. This paper studies the AGV path planning problem of a one-line production line in the workshop, establishes a mathematical model with the shortest transportation time as the objective function, and proposes an improved particle swarm optimization(IPSO) algorithm to obtain an optimal path. In order to be suitable for solving the path planning problem, we propose a new coding method based on this algorithm, design a crossover operation to update the particle position, and adopt a mutation mechanism to avoid the algorithm from falling into the local optimum. By calculating the shortest transportation time obtained, the improved algorithm is compared with other intelligent optimization algorithms. The experimental results show that the algorithm can improve the efficiency of AGV in material transportation and verify the effectiveness of related improvement mechanisms.
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