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A novel improved quantum genetic algorithm for robot coalition problem

Zhengyan Liu, Li Xu, Jieli Jiang, Shibing Wang

Year
2016
Citations
7

Abstract

Robot coalition problem is a complicated combinatorial optimization problem. In this paper, a novel improved quantum genetic algorithm for the problem is proposed. Based on quantum genetic algorithm, the new algorithm is mainly to improve the rotation angle of quantum gates. A new strategy is designed which can adaptively adjust the rotation angle according to the algorithm running state. Meanwhile, the new algorithm can automatically repair infeasible solution to feasible solution, and quantum mutation is introduced. Simulation results show that the improved algorithm has faster convergence rate and stronger global search capability, the performance is significantly better than quantum genetic algorithm.

Keywords

Genetic algorithmComputer scienceAlgorithmConvergence (economics)QuantumQuantum phase estimation algorithmMathematical optimizationQuantum computerRobotQuantum algorithm

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