The Research on Logistics Vehicle Path Optimization of Improved Ant Colony Algorithm

2012 ◽  
Vol 11 (1) ◽  
pp. 493-497
Author(s):  
Chang-Min Chen ◽  
Wei-Cheng Xie ◽  
Ling-Ling Li ◽  
Song-Song Fan ◽  
Wen-Bo Jiang
Keyword(s):  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Path Optimization ◽  
Vehicle Path ◽  
Improved Ant Colony Algorithm

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.

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.

scholarly journals Research on inventory path optimization of VMI large logistics enterprises based on ant colony algorithm

2021 ◽  
pp. 1-11
Author(s):  
Yaoyan Wang
Keyword(s):  
Ant Colony Algorithm ◽  
Time Window ◽  
Ant Colony ◽  
Path Optimization ◽  
Inventory Routing ◽  
Logistics System ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Logistics Enterprises ◽  
Improved Ant Colony Algorithm

Based on the idea of vendor management (VMI) inventory, this paper focuses on the integration and optimization of transportation and inventory control in large-scale logistics system, so as to minimize the total cost of the logistics system. Aiming at the inventory path optimization of VMI large logistics enterprises, based on ant colony algorithm, an improved ant colony algorithm, namely ant colony system algorithm, is designed to solve the model. The algorithm model combines deterministic selection and random selection to obtain a comprehensive probability, and combines local and global pheromone updating. In this paper, we study a two-level supply chain system with multiple customers from one supplier and inventory routing problem. According to the characteristics of inventory routing problem, a single cycle inventory path optimization model with time window constraint based on stochastic demand is established. The goal is to minimize the total system cost, including inventory cost of downstream customers, system transportation cost and penalty cost for not meeting the time window. According to the characteristics of the model, the ant colony algorithm is selected as the optimization method, and the improved ant colony algorithm is designed to solve the example, and the feasibility of the algorithm and model is verified.

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