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An improved quantum artificial fish swarm algorithm is proposed in this paper. Based on that quantum compu- ting have exponential acceleration for heuristic algorithm, by examining eight most recent patents and some literatures in the area of artificial fish swarm algorithm and quantum computing. The new algorithm uses qubits to code artificial fish and quantum revolving gate, preying behavior, following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, apply the new algorithm, the basic artificial fish swarm algorithm and the global edition artificial fish swarm algorithm to the simulation experiment high dimensional and complex non-convex programming respectively. The simulation results show that the improved algorithm can escape from the local extremum effectively, and has higher convergence speed and precision.

Solving High Dimensional and Complex Non-convex Programming Based on Improved Quantum Artificial Fish Algorithm