Research on the Reliability and Path Optimization of Three-Dimensional Warehousing Vehicles Based on Genetic-Ant Colony Algorithm

With the rapid development of the modern logistics and transportation industry, three-dimensional warehousing has increased. High-level selection vehicle is a storage vehicle. The category is an indispensable carrier tool in the three-dimensional ware housing. Operation efficiency is of great significance. At present, there are very few domestic high-end warehouse vehicles in the market, especially the rise height. Vehicles above 7M or more rely on imports. This article conducts a comprehensive research on the stability of the high-level selection of vehicles. First of all, abstract physical models that choose high-level vehicles, use the principles of Dalangbeel to establish a dynamic equation in different motion states, and use the prototype developed in this article as an example to analyze its dynamic stability. Secondly, the use of virtual prototype technology to dynamically simulate the motion of high -level vehicles, and compare the simulation results and theoretical results to verify the rationality of the kinetic model established. In addition, the tilt platform test method is used to verify the stability of the high-ranking vehicle prototype. In the end, in order to further improve the stability of the vehicle to pick up the vehicle and ensure the maneuverability of the vehicle, this article first proposes a high-level center of gravity self-balanced technology. According to the operating characteristics of the three-dimensional storage mid-to-high level, the mathematical model of the selection path of its three-dimensional space is established, and it is designed to construct a genetic-ant colony hybrid algorithm to solve it. The simulation results show that the algorithm has a strong global search ability and convergence performance, which better solves the problem of optimization of the operating path of high-level vehicles, improves its operating efficiency, and can save the battery energy of the vehicle to a certain extent, extend it to extend its Continuous operation time.

Authors

Institutions

Publication Details

Published
2024-08-29
DOI
https://doi.org/10.1109/icsece61636.2024.10729565
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the Reliability and Path Optimization of Three-Dimensional Warehousing Vehicles Based on Genetic-Ant Colony Algorithm

Yuyin Zhang, Chang Sun
Advanced Manufacturing and Logistics Optimization
article

Research on the Reliability and Path Optimization of Three-Dimensional Warehousing Vehicles Based on Genetic-Ant Colony Algorithm

Yuyin Zhang, Chang Sun
article en

Abstract

With the rapid development of the modern logistics and transportation industry, three-dimensional warehousing has increased. High-level selection vehicle is a storage vehicle. The category is an indispensable carrier tool in the three-dimensional ware housing. Operation efficiency is of great significance. At present, there are very few domestic high-end warehouse vehicles in the market, especially the rise height. Vehicles above 7M or more rely on imports. This article conducts a comprehensive research on the stability of the high-level selection of vehicles. First of all, abstract physical models that choose high-level vehicles, use the principles of Dalangbeel to establish a dynamic equation in different motion states, and use the prototype developed in this article as an example to analyze its dynamic stability. Secondly, the use of virtual prototype technology to dynamically simulate the motion of high -level vehicles, and compare the simulation results and theoretical results to verify the rationality of the kinetic model established. In addition, the tilt platform test method is used to verify the stability of the high-ranking vehicle prototype. In the end, in order to further improve the stability of the vehicle to pick up the vehicle and ensure the maneuverability of the vehicle, this article first proposes a high-level center of gravity self-balanced technology. According to the operating characteristics of the three-dimensional storage mid-to-high level, the mathematical model of the selection path of its three-dimensional space is established, and it is designed to construct a genetic-ant colony hybrid algorithm to solve it. The simulation results show that the algorithm has a strong global search ability and convergence performance, which better solves the problem of optimization of the operating path of high-level vehicles, improves its operating efficiency, and can save the battery energy of the vehicle to a certain extent, extend it to extend its Continuous operation time.

Changchun University (CN)
Openalex Percentile: Top 73%
Advanced Manufacturing and Logistics Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.