Ant Colony Optimization for the Traveling Salesman Problem Based on Ants with Memory

2008 ◽  
Author(s):  
Bifan Li ◽  
Lipo Wang ◽  
Wu Song
Keyword(s):  
Ant Colony Optimization ◽  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Ant Colony ◽  
The Traveling Salesman Problem ◽  
With Memory

scholarly journals Advanced Harmony Search with Ant Colony Optimization for Solving the Traveling Salesman Problem

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Ho-Yoeng Yun ◽  
Suk-Jae Jeong ◽  
Kyung-Sup Kim
Keyword(s):  
Ant Colony Optimization ◽  
Traveling Salesman Problem ◽  
Harmony Search ◽  
Solution Space ◽  
Global Optimum ◽  
Traveling Salesman ◽  
Ant Colony ◽  
Local Optimum ◽  
Optimum Solution ◽  
The Traveling Salesman Problem

We propose a novel heuristic algorithm based on the methods of advanced Harmony Search and Ant Colony Optimization (AHS-ACO) to effectively solve the Traveling Salesman Problem (TSP). The TSP, in general, is well known as an NP-complete problem, whose computational complexity increases exponentially by increasing the number of cities. In our algorithm, Ant Colony Optimization (ACO) is used to search the local optimum in the solution space, followed by the use of the Harmony Search to escape the local optimum determined by the ACO and to move towards a global optimum. Experiments were performed to validate the efficiency of our algorithm through a comparison with other algorithms and the optimum solutions presented in the TSPLIB. The results indicate that our algorithm is capable of generating the optimum solution for most instances in the TSPLIB; moreover, our algorithm found better solutions in two cases (kroB100 and pr144) when compared with the optimum solution presented in the TSPLIB.

Evolving Ant Colony Optimization

1998 ◽  
Vol 01 (02n03) ◽  
pp. 149-159 ◽  
Author(s):  
Hozefa M. Botee ◽  
Eric Bonabeau
Keyword(s):  
Genetic Algorithm ◽  
Combinatorial Optimization ◽  
Ant Colony Optimization ◽  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Ant Colony ◽  
New Approach ◽  
The Traveling Salesman Problem

Ant Colony Optimization (ACO) is a promising new approach to combinatorial optimization. Here ACO is applied to the traveling salesman problem (TSP). Using a genetic algorithm (GA) to find the best set of parameters, we demonstrate the good performance of ACO in finding good solutions to the TSP.

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