Abstract
Ant colony algorithms such as Ant Colony Optimization (ACO) have been effectively applied to solve the Traveling Salesman problem (TSP). However, traditional ACO algorithm has some issues such as long iterative length and prone to local convergence. To this end, we propose we embed ACO into Cultural Algorithm (CA) framework by leveraging the dual inheritance mechanism. Best solutions are evolved in both population space and belief space, and the communication between them is achieved by accept and influence operations. Besides, we employ multiple population spaces for parallel execution. Experiments show that the performance of our proposed algorithm is greatly improved.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
