TY - JOUR
A2 - Mao, Yuxin
AU - Qin, Guofeng
AU - Li, Jia
AU - Jiang, Nan
AU - Li, Qiyan
AU - Wang, Lisheng
PY - 2013
DA - 2013/12/10
TI - Warehouse Optimization Model Based on Genetic Algorithm
SP - 619029
VL - 2013
AB - This paper takes Bao Steel logistics automated warehouse system as an example. The premise is to maintain the focus of the shelf below half of the height of the shelf. As a result, the cost time of getting or putting goods on the shelf is reduced, and the distance of the same kind of goods is also reduced. Construct a multiobjective optimization model, using genetic algorithm to optimize problem. At last, we get a local optimal solution. Before optimization, the average cost time of getting or putting goods is 4.52996 s, and the average distance of the same kinds of goods is 2.35318 m. After optimization, the average cost time is 4.28859 s, and the average distance is 1.97366 m. After analysis, we can draw the conclusion that this model can improve the efficiency of cargo storage.
SN - 1024-123X
UR - https://doi.org/10.1155/2013/619029
DO - 10.1155/2013/619029
JF - Mathematical Problems in Engineering
PB - Hindawi Publishing Corporation
KW -
ER -