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A Self-adaption Quantum Genetic Algorithm Used in the Design of Command and ControlStructure

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DOI: 10.23977/iccsc.2017.1015


SUN Peng, WU Jun-sheng, ZHANG Jie-yong, LIAO Meng-chen

Corresponding Author

ZHANG Jie-yong


The paper mainly solved the problem of the design of command and control structure. First, the key elements in command and control structure are defined and we introduced the concept of work load of decision makers to describe the problem mathematically. Next, a mathematic model aimed at minimizing the root mean square of decision makers’ work load is developed. Finally, we combine the quantum genetic algorithm with self-adaption strategy and get the self-adaption quantum genetic algorithm. Major characteristic of this algorithm is adjusting the quantum rotation gate, generating the crossover probability and the mutation probability in a self-adaption way. Experimental results show that the self-adaption quantum genetic algorithm has a feature of evolving fast and searching precise, and it can cluster the platforms well to accomplish the design of command and control structure.


Work load, Root mean square, Quantum genetic algorithm, Self-adaption.

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