A Methodology and Modelling Technique for Taxi Path Optimization

2013 ◽  
Vol 711 ◽  
pp. 816-821
Author(s):  
Zhi Ping Hou ◽  
Feng Jin ◽  
Qin Jian Yuan ◽  
Yong Yi Li

Vehicle Routing Problem (VRP) is a typical combinatorial optimization problem. A new type of bionic algorithm-ant colony algorithm is very appropriate to solve Vehicle Routing Problem because of its positive feedback, robustness, parallel computing and collaboration features. In view of the taxi route optimization problem, this article raised the issue of the control of the taxi, by using the Geographic Information System (GIS), through the establishment of the SMS platform and reasonable taxi dispatch control center, combining ant colony algorithm to find the most nearest no-load taxi from the passenger, and giving the no-load taxi the best path to the passenger. Finally this paper use Ant Colony laboratory to give the simulation. By using this way of control, taxis can avoid the no-load problem effectively, so that the human and material resources can also achieve savings.

Author(s):  
Hongguang Wu ◽  
Yuelin Gao ◽  
Wanting Wang ◽  
Ziyu Zhang

AbstractIn this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.


2011 ◽  
Vol 219-220 ◽  
pp. 1285-1288 ◽  
Author(s):  
Chang Min Chen ◽  
Wei Cheng Xie ◽  
Song Song Fan

Vehicle routing problem (VRP) is the key to reducing the cost of logistics, and also an NP-hard problem. Ant colony algorithm is a very effective method to solve the VRP, but it is easy to fall into local optimum and has a long search time. In order to overcome its shortcomings, max-min ant colony algorithm is adopted in this paper, and its simulation system is designed in GUI of MATLAB7.0. The results show that the vehicle routing problem can well achieves the optimization of VRP by accessing the simulation data of database.


2013 ◽  
Vol 397-400 ◽  
pp. 2439-2446 ◽  
Author(s):  
Zheng Qiang Jiang ◽  
Yue Wu

Vehicle Routing Problem (VRP) plays a vital role in mathematical and logistics research. Its a typical NP-Hard problem, and ant colony algorithm has been proven to be an effect way in solving these problems. An improved ant colony algorithm is proposed to solve VRP on the basis of depth analyzing VRP and ant colony algorithm. It proposes the mathematical model of VRP and designs an improved ant colony algorithm, considering the inefficient solving, easy to partial stagnation shortcomings of ant colony algorithm and the attraction, repulsion, time constraint phenomena in VRP. This paper redesigns the pheromone update rule and the state transition rule and then it makes a simulation experiment by MATLAB programming, the results show that the improved ant colony is feasible and very valid in solving VRP.


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