Software College, Northeastern University, Shenyang, China

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Abstract—The Ant Colony Algorithm is an effective method for solving combinatorial optimization problems. However, in practical applications, there also exist issues such as slow convergence speed and easy to fall into local extremum. This paper proposes an improved Quantum Ant Colony Algorithm based on Bloch coordinates by combining Quantum Evolutionary Algorithm with Ant Colony Algorithm. In this algorithm, the current position information of ants is represented by the Bloch spherical coordinates of qubits; position update, position variation and random behavior of ants are all achieved with quantum rotation gate. Simulations of function extremum problem, TSP problem and QoS multicast routing problem were conducted, the results indicated that the algorithm could overcome prematurity, with a faster convergence speed and higher solution accuracy.

Index Terms—quantum computing, Ant Colony Algorithm, Quantum Ant Colony Algorithm

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Cite: Xiaofeng Chen, Xingyou Xia, and Ruiyun Yu, " Improved Quantum Ant Colony Algorithm based on Bloch Coordinates," Journal of Computers vol. 8, no. 6, pp. 1536-1543, 2013.