Research on optimization problem of the automated warehouse using an improved ant colony algorithm

Author(s):  
Meijuan Li ◽  
Xuebo Chen
2014 ◽  
Vol 543-547 ◽  
pp. 1681-1684 ◽  
Author(s):  
Ben Can Gong ◽  
Ting Yao Jiang ◽  
Shou Zhi Xu ◽  
Peng Chen

Traveling salesman problem (TSP) is not only a combinatorial optimization problem but also a classical NP-hard problem, which has high application value. Ant colony algorithm (ACA) is very effective for solving TSP problem, but basic ant colony algorithm has drawbacks of low convergence rate and easily trapping in local optimal solution. An improved ant colony algorithm was proposed. It used path optimization strategy to exchange the position of cities to find the better solution for TSP. Simulation results show the improved algorithm has better optimal solution and higher efficiency.


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