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考虑堆垛机加减速的节能自动立库设计
引用本文:欧阳永强,张新艳.考虑堆垛机加减速的节能自动立库设计[J].浙江大学学报(自然科学版 ),2019,53(9):1681-1688.
作者姓名:欧阳永强  张新艳
作者单位:同济大学 机械与能源工程学院,上海 201804
摘    要:以料箱式自动立库为研究对象,考虑堆垛机实际作业中存在的加减速过程,以能耗、平均吞吐时间和成本的计算模型为目标函数,以货架数量、货格数量和堆垛机的运行参数为决策变量,建立自动立库存储区多目标优化模型. 采用2种方法求解该多目标的混合整数非线性规划模型问题:使用经典遗传算法进行求解,得到不同权重下的解集;使用非支配排序遗传算法求取pareto解,得到非劣解的解集. 这些解集是优化后决策变量的集合,根据这些参数组合可以确定存储区的大小,并辅助货架与堆垛机的选购. 依据该模型的优化结果,可以设计出规划更合理的自动立库存储区,可为节能自动立库的建造提供有效参考.

关 键 词:自动立库(AS/RS)  存储区设计  多目标问题  能耗  参数优化  加减速  

Design of energy-saving automated storage and retrieval system considering acceleration and deceleration of storage and retrieval machine
Yong-qiang OUYANG,Xin-yan ZHANG.Design of energy-saving automated storage and retrieval system considering acceleration and deceleration of storage and retrieval machine[J].Journal of Zhejiang University(Engineering Science),2019,53(9):1681-1688.
Authors:Yong-qiang OUYANG  Xin-yan ZHANG
Abstract:A multi-objective optimization model studying storage area in mini-load AS/RS (automated storage and retrieval system) was raised. Take mini-load AS/RS as the research object, calculation models of energy consumption, average throughput time and cost of mini-load AS/RS as objective functions, and number of channels, number of storage compartment and operating parameters of the S/R (storage and retrieval) machine as the decision variables. Two methods were applied to solve the multi-objective mixed integer nonlinear programming model problem. One method used the classical genetic algorithm to get the solution set under different weights. Another method used non-dominated sorting genetic algorithm to obtain the pareto solution set. The solution set was the collection of optimized parameters, which determined the dimensions of storage system and helped to choose shelves and S/R machines. According to the optimal results of the model, storage area in AS/RS can be designed, which can provide reference for the construction of energy-saving AS/RS.
Keywords:automated storage and retrieval system (AS/RS)  design of storage area  multi-objective problem  energy consumption  parameter optimization  acceleration and deceleration  
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