scholarly journals Vehicle Routing Optimization of Tobacco Distribution Using Fuzzy C-Means Clustering and Ant Colony Algorithm

Author(s):  
Jiang-nan HAN ◽  
Qing-sheng SHI ◽  
Hong-chun HU
2013 ◽  
Vol 385-386 ◽  
pp. 1917-1920
Author(s):  
Rui Wang ◽  
Zai Tang Wang

This paper analyzes the domestic and international logistics distribution route optimization problem and the research status of ant colony algorithm, illustrates the problems existing in the logistics distribution now. It reflects the necessity to research on the vehicle routing optimization problem. In order to increasing the ant colony algorithm’s convergence speed and avoiding to fall into local optimum, we improve the pheromone evaporation coefficient and visibility to optimize the searching ability, which can avoid premature convergence and stagnation.


2014 ◽  
Vol 556-562 ◽  
pp. 4693-4696
Author(s):  
Yue Li Li ◽  
Ai Hua Ren

With the development of the market economy, the logistics industry has been developed rapidly.It is easy to understand that good vehicle travel path planning has very important significance in the logistics company,especially in the general production enterprises. This paper mainly studies the microcosmic traffic system in the type of vehicle routing problems: capacity-constrained vehicle routing problem. We demonstrate the use of Ant Colony System (ACS) to solve the capacitated vehicle routing problem, treated as nodes in a spatial network. For the networks where the nodes are concentrated, the use of hybrid heuristic optimization can greatly improve the efficiency of the solution. The algorithm produces high-quality solutions for the capacity-constrained vehicle routing problem.


2014 ◽  
Vol 556-562 ◽  
pp. 4005-4008
Author(s):  
Yue Li Li ◽  
Ai Hua Ren

With the development of the market economy, the logistics industry has been developed rapidly.It is easy to understand that good vehicle travel path planning has very important significance in the logistics company,especially in the general production enterprises. This paper mainly studies the microcosmic traffic system in the type of vehicle routing problems: capacity-constrained vehicle routing problem. We demonstrate the use of Ant Colony System (ACS) to solve the capacitated vehicle routing problem, treated as nodes in a spatial network. For the networks where the nodes are concentrated, the use of hybrid heuristic optimization can greatly improve the efficiency of the solution. The algorithm produces high-quality solutions for the capacity-constrained vehicle routing problem.


2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Ming Meng ◽  
Yun Ma

Under the background of severe air pollution and energy shortage, electric vehicles (EVs) are promising vehicles to support green supply chain and clean production. In the world, the renewal of EVs has become a general trend. Therefore, the concern about EVs is a hot issue at present, but EVs have the characteristics of limited driving distance and long charging time. When the EVs are used in logistics transportation, these characteristics have a significant impact on the vehicle routing problems. Therefore, based on the research experience of traditional vehicle routing optimization, combining with the characteristics of EVs, this paper presents an optimal problem of electric vehicle routes with time windows based on two charging methods and it also designs a mathematical model which was caused by early and late arrival as the objective function to minimize the transportation cost, vehicle use cost, power supply cost, and penalty cost. The model is solved using an ant colony algorithm. Finally, the ant colony algorithm is tested and analysed with an example.


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