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- Title
A FUZZY HYBRID GA-PSO ALGORITHM FOR MULTI-OBJECTIVE AGV SCHEDULING IN FMS.
- Authors
Mousavi, M.; Yap, H. J.; Musa, S. N.; Dawal, S. Z. M.
- Abstract
An automated guided vehicle (AGV) is a mobile robot with remarkable industrial applicability for transporting materials within a manufacturing facility or a warehouse. AGV scheduling refers to the process of allocating AGVs to tasks, taking into account the cost and time of operations. Multi- objective scheduling is adopted in this study to acquire a more complex and combinatorial model in contrast with single objective practices. The model objectives are the makespan and number of AGVs minimization while considering the AGVs battery charge. A fuzzy hybrid GA-PSO (genetic algorithm -- particle swarm optimization) algorithm was developed to optimize the model. Results have been compared with GA, PSO, and hybrid GA-PSO algorithms to explore the applicability of the algorithm developed. Model's feasibility and the algorithms' performance were investigated through a numerical example before and after the optimization. The model evaluation and validation was conducted through simulation via Flexsim software. The fuzzy hybrid GA-PSO surpassed the other methods, although obtaining less mean computational time was the only significant improvement over hybrid GA-PSO.
- Subjects
AUTOMATED guided vehicle systems; AUTOMATED planning &; scheduling; GENETIC algorithms; PARTICLE swarm optimization; COMPUTER simulation
- Publication
International Journal of Simulation Modelling (IJSIMM), 2017, Vol 16, Issue 1, p58
- ISSN
1726-4529
- Publication type
Article
- DOI
10.2507/IJSIMM16(1)5.368