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Journal of System Simulation

Abstract

Abstract: Based on the dynamic storage allocation strategy, the two-stage optimization model is constructed with the whole warehouse as the main optimization body, in order to meet the safety and rationality of the storage allocation goals, and to meet the dispatching goals of the shortest operation time and the lowest energy consumption of each stacke. The upper and lower levels of the model are typical multi-objective optimization problems, and the ideal solution of the upper level model will be the initial condition of the lower level model. The multi-objective genetic algorithm is used to solve the ideal solution of the optimization model, and the entropy weight method is used to assign weights to each objective. The final results show that there is no significant difference between dynamic and static allocation strategies under the discrete arrangement of goods, but the comprehensive optimization effect of dynamic allocation strategy on cargo location allocation and stacker scheduling under the aggregate arrangement is significantly better than that of static allocation, and the quality of goods affects the overall optimization effect. In the case of large mass, the safety optimization effect is more obvious, while in the case of small mass, the rationality and the optimization effect of stacker scheduling are more obvious.

First Page

1435

Last Page

1448

CLC

TP391.9

Recommended Citation

Chen Juan, Zheng Wang, Liu Qianqian, et al. Automatic Multi-objective Optimization Based on Dynamic Storage Location Allocation Strategy[J]. Journal of System Simulation, 2025, 37(6): 1435-1448.

Corresponding Author

Zheng Wang

DOI

10.16182/j.issn1004731x.joss.24-0210

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