HEURISTIC QUANTUM GENETIC ALGORITHM FOR AIR COMBAT DECISION MAKING ON COOPERATIVE MULTIPLE TARGET ATTACK

Author:

KONG HAIPENG1,LI NI1

Affiliation:

1. School of Automation Science and Electrical Engineering, Beihang University, 100191, Beijing, P. R. China

Abstract

In order to achieve the optimal attack outcome in the air combat under the beyond visual range (BVR) condition, the decision-making (DM) problem which is to set a proper assignment for the friendly fighters on the hostile fighters is the most crucial task for cooperative multiple target attack (CMTA). In this paper, a heuristic quantum genetic algorithm (HQGA) is proposed to solve the DM problem. The originality of our work can be supported in the following aspects: (1) the HQGA assigns all hostile fighters to every missile rather than fighters so that the HQGA can encode chromosomes with quantum bits (Q-bits); (2) the relative successful sequence probability (RSSP) is defined, based on which the priority attack vector is constructed; (3) the HQGA can heuristically modify quantum chromosomes according to modification technique proposed in this paper; (4) last but not the least, in some special conditions, the HQGA gets rid of the constraint described by other algorithms that to obtain a better result. In the end of this paper, two examples are illustrated to show that the HQGA has its own advantage over other algorithms when dealing with the DM problem in the context of CMTA.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Science Applications,Modeling and Simulation

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Design and Verification of UAV Maneuver Decision Simulation System Based on Deep Q-learning Network;2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV);2020-12-13

2. An optimization method for task assignment for industrial manufacturing organizations;Applied Intelligence;2017-05-17

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