Abstract
The order-picking processes of fixed shelves in a warehouse system require high speed and efficiency. In this study, a novel fast genetic algorithm was proposed for constrained multi-objective optimization problems. The handling of constraint conditions were distributed to the initial population generation and each genetic process. Combine the constraint conditions and objectives, a new partial-order relation was introduced for comparison of individuals. This novel algorithm was used to optimize the stacker picking path in an Automated Storage/Retrieve System (AS/RS) of a large airport. The simulation results indicates that the proposed algorithm reduces the computational complexity of time and space greatly, and meets the needs of practical engineering of AS/RS optimization control.
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© 2015 Springer International Publishing Switzerland
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Ma, Y., Li, Z., Yun, W. (2015). Fast Genetic Algorithm for Pick-up Path Optimization in the Large Warehouse System. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9142. Springer, Cham. https://doi.org/10.1007/978-3-319-20469-7_5
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DOI: https://doi.org/10.1007/978-3-319-20469-7_5
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-20468-0
Online ISBN: 978-3-319-20469-7
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