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Originated by a real-world case study from the automotive industry, this paper attempts to address the assembly lines balancing problem with human-robot collaboration and heterogeneous operators while optimizing the cycle time. A genetic algorithm (GA) with customized parameters and features is proposed while considering the characteristics of the problem. The computational results show that the developed GA can provide the decision-makers with efficient solutions with heterogeneous humans and robots. Furthermore, the results reveal that the cycle time is highly influenced by order of the operators’ skills, particularly when a fewer number of humans and robots exist at the stations. CC BY-NC-ND 4.0Corresponding author: Amir NourmohammadiEdited by Emanuele Carpanzano, Claudio Boër, Anna ValenteThis study is funded by the Knowledge Foundation (KKS), Sweden, through the VF-KDO and ACCURATE 4.0 projects at the University of Skövde, Sweden. VF-KDO ACCURATE 4.0 |
