An Improved Ant Colony Algorithm to Solve Vehicle Routing Problem with Time Windows

2015 ◽  
pp. 11-22 ◽  
Author(s):  
Yi Yunfei ◽  
Lin Xiaodong ◽  
Sheng Kang ◽  
Cai Yongle
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Time Windows ◽  
Ant Colony ◽  
Routing Problem ◽  
Improved Ant Colony Algorithm

scholarly journals A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows

2021 ◽  
Author(s):  
Hongguang Wu ◽  
Yuelin Gao ◽  
Wanting Wang ◽  
Ziyu Zhang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Ant Colony ◽  
Routing Problem ◽  
Multiple Strategies ◽  
Hard Time ◽  
Mutation Operation

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.

The Research on Vehicle Routing Problem Based on Improved Ant Colony Algorithm

2013 ◽  
Vol 397-400 ◽  
pp. 2439-2446 ◽  
Author(s):  
Zheng Qiang Jiang ◽  
Yue Wu
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Vital Role ◽  
Ant Colony ◽  
Transition Rule ◽  
Routing Problem ◽  
Np Hard Problem ◽  
Matlab Programming ◽  
Improved Ant Colony Algorithm

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.

A Improved Pareto of Ant Colony Algorithm to Solve the Vehicle Routing Problem with Time Windows

2014 ◽  
Vol 1030-1032 ◽  
pp. 1941-1944
Author(s):  
Hong Dou Zhang ◽  
Ning Guo ◽  
Jian Lin Mao ◽  
Hai Feng Wang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Transition Probability ◽  
Time Windows ◽  
Optimal Solution ◽  
Ant Colony ◽  
Local Optimum ◽  
Routing Problem ◽  
Important Extension

Vehicle routing problem with time Windows (VRPTW) that is a kind of important extension type for VPR. In view of problem which the ant colony algorithm in solving VRPTW easily plunged into local optimum , this paper defines a new ant transition probability of saving ideas, and uses the Pareto optimal solution set of global pheromone updating rule, and puts forward a kind of improved Pareto ant colony algorithm (IPACA) . Through the simulation experiments show that IPACA improves the global search ability of ACA, effectively avoids the algorithm falls into local optimum, and reduces the total distribution cost (distance), so as to verify the effectiveness of the proposed algorithm.

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