Abstract
The efficiency of automatic guided vehicle (AGV) scheduling is important to improve the productivity of manufacturing enterprises. In this paper, the production materials and cutting tools consumables are transferred by multiple AGVs and a multi-objective mathematical model of AGV scheduling is established, which contains three objectives, i.e., the total travel distance of AGVs, the standard deviation of AGVs workload and the standard deviation of the difference between the latest delivery time and the predicted time of tasks. Then, an improved harmony search (HS) algorithm is proposed by adopting dynamic changing harmony memory considering rate (HMCR) parameters and implementing neighborhood search strategy for the best harmony in harmony memory (HM). Meanwhile, the harmony is divided into several segments according to the capacitated multiple-load AGVs. Each segment corresponds to the tasks execution scope of AGVs that return to the warehouse in turn. And the elements sequence of each segment represents the order of these tasks performed by AGV. At the same time, calculating the fitness value in each segment of harmony, and finally adding them up as the total fitness value of the whole harmony. A larger-scale instance from the real-life manufacturing enterprise is used to evaluate the performance of the proposed HS algorithm. The computational results show that the proposed HS algorithm outperforms the current solution.
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Acknowledgements
This research is supported by the National Natural Science Foundation of China (NSFC) under Grant Nos. 51825502, 51775216 and 51721092, the Natural Science Foundation of Hubei Province under Grant No. 2018CFA078, and Program for HUST Academic Frontier Youth Team.
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Li, G., Li, X., Gao, L. et al. Tasks assigning and sequencing of multiple AGVs based on an improved harmony search algorithm. J Ambient Intell Human Comput 10, 4533–4546 (2019). https://doi.org/10.1007/s12652-018-1137-0
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DOI: https://doi.org/10.1007/s12652-018-1137-0