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.

Research on Improved Ant Colony Algorithm for the Optimization of the Large Storage Picking Path Based on RFID

2012 ◽  
Vol 239-240 ◽  
pp. 1348-1351 ◽  
Author(s):  
Pei Zhi Wen ◽  
Yong Bo Wang ◽  
Li Fang Li
Keyword(s):  
Dynamic Response ◽  
High Precision ◽  
Ant Colony Algorithm ◽  
Parameter Selection ◽  
Ant Colony ◽  
Path Optimization ◽  
Response Strategy ◽  
Waiting Strategy ◽  
Candidate Set ◽  
Improved Ant Colony Algorithm

For the realtime updating and strong randomness of the information, large RFID-based warehousing picking path optimization job requires to make decision continuously. It is different from the traditional picking path Problem. This paper proposed an Improved Ant Colony algorithm in order to solve the optimization of the large storage picking path based on RFID. Distributed Strategy, Dynamic Response Strategy and Time Waiting Strategy are adopted to improve the candidate set, meanwhile, adjust operator and parameter selection. Experimental results show that the convergence speed of this algorithm with high precision, a better solution to the optimization of picking operation based on RFID.

Logistics Terminal Distribution Mode and Path Optimization Based on Ant Colony Algorithm

2018 ◽  
Vol 102 (4) ◽  
pp. 2969-2985 ◽  
Author(s):  
Miao Yu ◽  
Guojun Yue ◽  
Zichen Lu ◽  
Xu Pang
Keyword(s):  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Path Optimization ◽  
Distribution Mode
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