基于病毒进化遗传算法的大型机场货位动态优化策略

Jiandong Qiu, Kaiyue Zhang, Minan Tang
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引用次数: 0

摘要

大型机场自动化立体仓库在物流中占有重要地位,其中货物进出效率是最重要的部分。货位优化是提高物流效率的有效方法。通过对大型机场货运站散货处理系统结构和工作特点的比较分析,建立了货位动态优化问题的模型。选择病毒进化遗传算法(VEGA)进行优化仿真,并根据实际优化条件设计耗时规则。根据实际优化条件,设计了基于耗时规则的货位编号规则。仿真结果表明,与传统遗传算法相比,VEGA的收敛速度和计算速度都有明显提高,能够更好地满足该领域的实际需要。
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Dynamic Optimization Strategy of Large Airport Cargo Location based on Virus Evolutionary Genetic Algorithm
The automated stereoscopic warehouse of large airport plays an important role in logistics, in which cargo access efficiency is the most important part. And cargo location optimization is an effective method to improve its efficiency. After comparing and analysing the structure and working characteristics of bulk cargo processing system in large airport cargo station, the dynamic optimization problem of the cargo location was modelled. The virus evolutionary genetic algorithm (VEGA) was selected for optimization simulation, and the time-consuming rule was designed according to the actual optimization conditions. A cargo location numbering rule based on time-consuming rule was designed according to the actual optimization conditions. Simulation results show that both the convergence and calculating speeds of the VEGA have been obviously improved compared with those of the traditional genetic algorithm, which can meet the actual needs of the field better.
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来源期刊
EEA - Electrotehnica, Electronica, Automatica
EEA - Electrotehnica, Electronica, Automatica Engineering-Electrical and Electronic Engineering
CiteScore
0.90
自引率
0.00%
发文量
26
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