Dynamic Optimization Strategy of Large Airport Cargo Location based on Virus Evolutionary Genetic Algorithm

被引：0

作者：

Qiu J. ^{[1
]}

Zhang K. ^{[2
]}

Tang M. ^{[3
]}

机构：

[1] School of Mechanical and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou

[2] School of energy and transportation systems, Peter the Great St.Petersburg Polytechnic University, St.Petersburg

[3] School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou

来源：

EEA - Electrotehnica, Electronica, Automatica | 2022年 / 70卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Cargo location optimization; Stereoscopic warehouse; Time-consuming rule; Virus evolutionary genetic algorithm;

D O I：

10.46904/eea.22.70.1.1108008

中图分类号：

学科分类号：

摘要：

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. © 2022, Editura ELECTRA. All rights reserved.

引用

页码：73 / 83

页数：10

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