A Method for Solving Optimization Problem in Continuous Space Using Improved Ant Colony Algorithm

2005 ◽  
pp. 61-70 ◽  
Author(s):  
Ling Chen ◽  
Jie Shen ◽  
Ling Qin ◽  
Jin Fan
Keyword(s):  
Optimization Problem ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Continuous Space ◽  
Improved Ant Colony Algorithm

An Improved Ant Colony Algorithm Based on Path Optimization Strategy for TSP

2014 ◽  
Vol 543-547 ◽  
pp. 1681-1684 ◽  
Author(s):  
Ben Can Gong ◽  
Ting Yao Jiang ◽  
Shou Zhi Xu ◽  
Peng Chen
Keyword(s):  
Optimization Problem ◽  
Ant Colony Algorithm ◽  
Optimal Solution ◽  
Ant Colony ◽  
Path Optimization ◽  
Optimization Strategy ◽  
Local Optimal Solution ◽  
Np Hard Problem ◽  
Improved Ant Colony Algorithm ◽  
High Application

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.

Cross-country path planning based on improved ant colony algorithm

2013 ◽  
Vol 33 (4) ◽  
pp. 1157-1160
Author(s):  
Tianyi WU ◽  
Jiheng XU ◽  
Jianyong LIU
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Cross Country ◽  
Improved Ant Colony Algorithm
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