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Enhanced migrating birds optimization algorithm for U-shaped assembly line balancing problems with workers assignment

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Abstract

U-shaped assembly lines have been popularly adopted in electronics and appliances to improve their flexibility and efficiency. However, most past studies assumed that the processing time of each task is fixed and hence just considered the task allocation but ignored worker assignment. In this paper, the processing time of each task depends on the workers and then the cooperative optimization of task allocation and workers assignment is considered in U-shaped assembly line balancing problems to optimize the cycle time. Later, an enhanced migrating birds optimization algorithm (EMBO) is proposed to solve it. In the EMBO algorithm, since this new problem has two subproblems: task allocation and worker assignment, the prevent work designs two neighborhood structures to improve the leader and following birds. Furthermore, the temperature acceptance criteria, to judge whether the neighbor replaces current following bird, are developed to ensure the diversity of population and avoid being trapped in the local optimum. And a competitive mechanism is introduced to increase the probability of the promising birds locating in the front of the line. The proposed algorithm is compared with other well-known algorithms in the literature, and the numerical results demonstrate that the proposed algorithm outperforms other algorithms.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their helpful comments and constructive suggestions. This work is supported by National Natural Science Foundation of China (Nos. 51275366, 51305311).

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Correspondence to Qiuhua Tang.

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Zhang, Z., Tang, Q., Han, D. et al. Enhanced migrating birds optimization algorithm for U-shaped assembly line balancing problems with workers assignment. Neural Comput & Applic 31, 7501–7515 (2019). https://doi.org/10.1007/s00521-018-3596-9

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