Quantum Dynamic Mechanism-based Parallel Ant Colony Optimization Algorithm

Quantum Dynamic Mechanism-based Parallel Ant Colony Optimization Algorithm

A novel Parallel Ant Colony Optimization Algorithm based on Quantum dynamic mechanism for traveling salesman problem (PQACO) is proposed. The use of the improved 3-opt operator provides this methodology with superior local search ability; several antibody diversification schemes were incorporated into the PQACO in order to improve the balance between exploitation and exploration. We describe th...

Quantum-inspired Ant Colony Optimization Algorithm

To enhance the optimization ability of ant colony optimization, this paper proposes a Bloch sphere-based quantum-inspired ant colony optimization algorithm. In the proposed approach, the positions of ants are encoded by qubits described on Bloch sphere. First, the destinations of ants are obtained by the select probability designed by the pheromone and heuristic information, and then, the movem...

A Parallel Ant Colony Optimization Algorithm Based on Crossover Operation

Quantum ant colony optimization algorithm based onBloch spherical search

-In the existing quantum-behaved optimization algorithms, almost all of the individuals are encoded by qubits described on plane unit circle. As qubits contain only a variable parameter, quantum properties have not been fully embodied, which limits the optimization ability rise further. In order to solve this problem, this paper proposes a quantum ant colony optimization algorithm based on Bloc...

Ant Colony Optimization Algorithm

Hybrid algorithm is proposed to solve combinatorial optimization problem by using Ant Colony and Genetic programming algorithms. Evolutionary process of Ant Colony Optimization algorithm adapts genetic operations to enhance ant movement towards solution state. The algorithm converges to the optimal final solution, by accumulating the most effective sub-solutions.