A Self-adaption Quantum Genetic Algorithm Used in the Design of Command and ControlStructure
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DOI: 10.23977/iccsc.2017.1015
Author(s)
SUN Peng, WU Jun-sheng, ZHANG Jie-yong, LIAO Meng-chen
Corresponding Author
ZHANG Jie-yong
ABSTRACT
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.
KEYWORDS
Work load, Root mean square, Quantum genetic algorithm, Self-adaption.