scholarly journals Machining Path Optimization of 3C Locking Robots Using Adaptive Ant Colony Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jiayuan Luo ◽  
Xiangyang Xu ◽  
Peitang Wei ◽  
Chengxiang Shi ◽  
Guofeng Liu
Keyword(s):  
Optimization Model ◽  
Ant Colony ◽  
Path Optimization ◽  
Distributed Environment ◽  
Machining Performance ◽  
Adaptive Function ◽  
Theoretical Support ◽  
Hole Position ◽  
Bolt Holes ◽  
Design Guidance

The motion smoothness of 3C locking robot directly affects the machining performance. Improving the motion smoothness can optimize the motion trajectory and reduce the processing time. In this paper, a novel machining path optimization model including motion smoothness is built by employing the coordinate boundary of velocity and acceleration after evaluating the machining motion smoothness of the 3C locking robot. Secondly, based on the creation of the ant colony of adaptive function algorithm, the optimization model of the 3C locking robot in the situation of fixed bolt hole position and floating bolt hole position is resolved. Lastly, the proposed approach collects and analyses a huge amount of data to enable robots to make on-the-fly decisions in the middle of production, even when faced with unexpected circumstances. In the Spark distributed environment, we use the conventional K clustering technique to improve the final output utilizing clustering means. The results show that the machining path optimization of fixed hole considering the motion smoothness improves the smoothness but extends the machining path; the cooperative machining path optimization of multiregion floating bolt holes can significantly improve the motion smoothness and effectively reduce the length of the path. The research results provide theoretical support and design guidance for designers.

scholarly journals The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Liyi Zhang ◽  
Ying Wang ◽  
Teng Fei ◽  
Hongwei Ren
Keyword(s):  
Carbon Emissions ◽  
Optimization Model ◽  
Ant Colony Algorithm ◽  
Optimization Problems ◽  
Ant Colony ◽  
Path Optimization ◽  
Low Carbon ◽  
Economic Activities ◽  
Logistics Industry ◽  
Routing Optimization

As the energy conservation and emission reduction and sustainable development have become the hot topics in the world, low carbon issues catch more and more attention. Logistics, which is one of the important economic activities, plays a crucial role in the low carbon development. Logistics leads to some significant issues about consuming energy and carbon emissions. Therefore, reducing energy consumption and carbon emissions has become the inevitable trend for logistics industry. Low carbon logistics is introduced in these situations. In this paper, from the microcosmic aspects, we will bring the low carbon idea in the path optimization issues and change the amount of carbon emissions into carbon emissions cost to establish the path optimization model based on the optimization objectives of the lowest cost of carbon emissions. According to different levels of air pollution, we will establish the double objectives path optimization model with the consideration of carbon emissions cost and economy cost. Use DNA-ant colony algorithm to optimize and simulate the model. The simulation indicates that DNA-ant colony algorithm could find a more reasonable solution for low carbon logistics path optimization problems.

The Research about Simulated Annealing Ant Colony Algorithm in Emergency Logistics Path Optimization

2012 ◽  
Vol 482-484 ◽  
pp. 2470-2474 ◽  
Author(s):  
Li Yi Zhang ◽  
Teng Fei ◽  
Yun Shan Sun
Keyword(s):  
Simulated Annealing ◽  
Optimization Model ◽  
Economic Benefit ◽  
Ant Colony Algorithm ◽  
High Efficiency ◽  
Ant Colony ◽  
Path Optimization ◽  
Logistics Distribution ◽  
Emergency Logistics

Emergency logistics distribution, as an important role, is the key to the whole logistics. Emergency logistics is mainly reflected in emergency. For the disaster, economic benefit is not the first thing to be thought about. High efficiency is the key to emergency logistics. This article concentrates on path optimization of emergency logistics distribution. Propose emergency logistics distribution path optimization model which considers timeliness as the first goal. Utilize Simulated Annealing Ant Colony Algorithm to search for optimization. Based on simulation, Simulated Annealing Ant Colony Algorithm owns better timeliness to solve emergency logistics distribution.

scholarly journals Based On Evacuation Entropy Ant Colony Evacuation Path Optimization Model Considering Classified Crowds

2019 ◽  
Vol 267 ◽  
pp. 052026
Author(s):  
Fang Wang ◽  
Jian Wang ◽  
Xiaowei Chen
Keyword(s):  
Optimization Model ◽  
Ant Colony ◽  
Path Optimization

Study of delivery path optimization solution based on improved ant colony model

2021 ◽  
Author(s):  
Ruixiao Huang ◽  
Jingyuan Ning ◽  
Zhenghao Mei ◽  
Xudong Fang ◽  
Xiaomei Yi ◽  
...  
Keyword(s):  
Ant Colony ◽  
Path Optimization

scholarly journals Vehicle logistics path optimization based on ant colony and particle hybrid algorithm

2021 ◽  
Vol 1865 (4) ◽  
pp. 042086
Author(s):  
Jing Jiang ◽  
Ning Yu ◽  
Jinping Ye ◽  
Wei Bai
Keyword(s):  
Hybrid Algorithm ◽  
Ant Colony ◽  
Path Optimization

scholarly journals Contactless Distribution Path Optimization Based on Improved Ant Colony Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Feng Wu
Keyword(s):  
Customer Service ◽  
User Satisfaction ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Cost Model ◽  
Ant Colony ◽  
Path Optimization ◽  
Traffic Information ◽  
Research Areas ◽  
Improved Ant Colony Algorithm

In the context of the normalization of the epidemic, contactless delivery is becoming one of the most concerned research areas. In the severe epidemic environment, due to the frequent encounter of bayonet temperature measurement, road closure, and other factors, the real-time change frequency of each traffic information is high. In order to improve the efficiency of contactless distribution and enhance user satisfaction, this paper proposes a contactless distribution path optimization algorithm based on improved ant colony algorithm. First of all, the possible traffic factors in the epidemic environment were analyzed, and the cost of each link in the distribution process was modeled. Then, the customer satisfaction is analyzed according to the customer service time window and transformed into a cost model. Finally, the total delivery cost and user satisfaction cost were taken as the optimization objectives, and a new pheromone updating method was adopted and the traditional ant colony algorithm was improved. In the experiment, the effectiveness of the proposed model and algorithm is verified through the simulation optimization and comparative analysis of an example.

Comparison of GA, ACO algorithm, and PSO algorithm for path optimization on free-form surfaces using coordinate measuring machines

2021 ◽  
Author(s):  
Yueping Chen ◽  
Naiqi Shang
Keyword(s):  
Optimization Algorithm ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Path Optimization ◽  
Inspection Time ◽  
Free Form ◽  
Coordinate Measuring Machines ◽  
Ant Colony Optimization Algorithm ◽  
Measuring Machine ◽  
Free Form Surfaces

Abstract Coordinate measuring machines (CMMs) play an important role in modern manufacturing and inspection technologies. However, the inspection process of a CMM is recognized as time-consuming work. The low efficiency of coordinate measuring machines has given rise to new inspection strategies and methods, including path optimization. This study describes the optimization of an inspection path on free-form surfaces using three different algorithms: an ant colony optimization algorithm, a genetic algorithm, and a particle swarm optimization algorithm. The optimized sequence of sampling points is obtained in MATLAB R2020b software and tested on a Leitz Reference HP Bridge Type Coordinate Measuring Machine produced by HEXAGON. This study compares the performance of the three algorithms in theoretical and practical conditions. The results demonstrate that the use of the three algorithms can result in a collision-free path being found automatically and reduce the inspection time. However, owing to the different optimization methodologies, the optimized processes and optimized times of the three algorithms, as well as the optimized paths, are different. The results indicate that the ant colony algorithm has better performance for the path optimization of free-form surfaces.

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