The Planning of the Dynamic Path of the 3rd Party Logistics Center, which Based on the Ant Colony Optimization

2012 ◽  
Vol 253-255 ◽  
pp. 1472-1475
Author(s):  
Yue Ran Zhen ◽  
Jia Cheng Huang ◽  
Wen Yong Li ◽  
Fu Xiang Li ◽  
Yang Zhang

Logistics profits which is the third profit source, it has become a "black hole" of the profits of the entire supply chain. At all the logistics costs, the proportion of transport costs is approximately 35% to 60%, thus by through reducing transportation costs, can we improve the effectiveness of the logistics system, and finally to maximize profits. Dynamic path planning of third-party logistics centers undoubtedly reduces transportation costs and optimizes logistics management research priority. The article first introduces the TSP and VRP, both are classic path planning methods, and then through the basic idea and the basic principles of detailing the Ant colony optimization to illustrate the wide range of applications of it in third-party logistics.

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 62107-62115 ◽  
Author(s):  
Qi Song ◽  
Qinglei Zhao ◽  
Shuxin Wang ◽  
Qiang Liu ◽  
Xiaohe Chen

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zhen Wang ◽  
Jianqing Li ◽  
Manlin Fang ◽  
Yang Li

With the rapid growth in the number of vehicles, energy consumption and environmental pollution in urban transportation have become a worldwide problem. Efforts to reduce urban congestion and provide green intelligent transport become a hot field of research. In this paper, a multimetric ant colony optimization algorithm is presented to achieve real-time dynamic path planning in complicated urban transportation. Firstly, four attributes are extracted from real urban traffic environment as the pheromone values of ant colony optimization algorithm, which could achieve real-time path planning. Then Technique for Order Preference by Similarity to Ideal Solution methods is adopted in forks to select the optimal road. Finally, a vehicular simulation network is set up and many experiments were taken. The results show that the proposed method can achieve the real-time planning path more accurately and quickly in vehicular networks with traffic congestion. At the same time it could effectively avoid local optimum compared with the traditional algorithms.


Author(s):  
Mohammad Mirabi ◽  
Parya Seddighi

AbstractThe hub location problems involve locating facilities and designing hub networks to minimize the total cost of transportation (as a function of distance) between hubs, establishing facilities and demand management. In this paper, we consider the capacitated cluster hub location problem because of its wide range of applications in real-world cases, especially in transportation and telecommunication networks. In this regard, a mathematical model is presented to address this problem under capacity constraints imposed on hubs and transportation lines. Then, a new hybrid algorithm based on simulated annealing and ant colony optimization is proposed to solve the presented problem. Finally, the computational experiments demonstrate that the proposed heuristic algorithm is both effective and efficient.


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