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《Journal of Xiamen University(Natural Science)》 2010-03
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Modeling and Optimization of Lift Transport Systems Based on Improved GA

LUO Jian,SU Hai-dun,HE Shan-jun,WU Chang-qing(School of Information Science and Technology,Xiamen University,Xiamen 361005,China)  
To improve the efficiency of the lift in autonomous vehicle storage and retrieval systems,an optimization methods based on improved genetic algorithm is proposed.A mathematical model of the lift system is built and a improved genetic algorithm is adopted to get an near optimal solution of the scheduling in the AVS/RS.With this algorithm,objective functions,set respectively as the minimum total waiting time of RGV,the minimum overall running time of the lift,and the minimum linear weighted sum of the above two are simulated.Finally,the validity of the algorithm is illustrated by a case study.
【CateGory Index】: TH242
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