Cooperative multi-aircraft target distribution method based on hybrid optimization algorithm

Abstract

The invention provides a cooperative multi-aircraft target distribution method based on a hybrid optimization algorithm. The method comprises the following steps that (11) flying fuel consumption and flying time and length of each Chinese aircraft are collected; (12) a fitness function in a discrete particle swarm optimization is built; (13) target distribution is conducted on the Chinese aircrafts according to the discrete particle swarm optimization. The cooperative multi-aircraft target distribution method based on the hybrid optimization algorithm can cope with battlefield situations constantly changing and quickly determine target distribution schemes, and guarantees real-time performance of the hybrid optimization algorithm; meanwhile, the distribution schemes can be consistent with the reality and be verified in the follow-up path planning process, and guarantee applicability of the algorithm.

Description

technical field [0001] The invention relates to the field of computer aided air combat and electronic simulated air combat, in particular to a multi-aircraft cooperative target allocation method based on a hybrid optimization algorithm. Background technique [0002] The target allocation algorithm is one of the key technologies for multi-aircraft cooperative operations. It is mainly based on the battlefield situation to rationally allocate enemy targets and effectively improve the overall combat effectiveness of the battlefield. Target assignment is a complex combinatorial optimization problem with numerous constraints, and its solution space grows geometrically with the increase of the total number of weapons and tasks, making it a multi-parameter, multi-constraint NP problem. [0003] The traditional solution method is to simplify the target allocation problem into a mathematical programming model, and then use exhaustive method, dynamic programming, branch and bound and o...

AI Technical Summary

Problems solved by technology

[0008] 1) Since the allocation strategy itself has not been improved, the allocation scheme obtained simply by taking the task cost as the optimization goal has poor ability to adapt to environmental changes

At the same time, on the modern battlefield, it is necessary to deal with the rapidly changing battlefield situation. Changes in the situation may reduce the efficiency of the original allocation plan or even make it unfeasible.

[0009] Although the solution speed and accuracy of the target allocation problem have been greatly improved, the optimized results may not be consistent with reality, or the optimized results may be denied in the subsequent path planning

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