Cooperative air combat firepower distribution method based on improved multi-target leapfrog algorithm

Abstract

The invention provides a cooperative air combat firepower distribution method based on an improved multi-target leapfrog algorithm and belongs to the technical field of computer simulation and method optimization. The method comprises the steps that firstly, required data information is obtained through a cooperative air combat formation command and control system; secondly, a multi-target optimization module of cooperative air combat firepower distribution is established; then a multi-target quantum leapfrog algorithm based on a self-adaptive mesh method is carried out, and a Pareto non-inferior solution of firepower distribution problem is solved; finally, rules can be selected independently according to the optimal distribution scheme, and the optimal firepower distribution scheme is selected from the non-inferior solution. The cooperative air combat firepower distribution method based on the improved multi-target leapfrog algorithm has the major functions that weapons on a fighter aircraft on an attack mission are distributed to multiple targets according to the optimal firepower distribution scheme, the formed cooperative air combat is enabled to realize the optimal cooperative attack effect, and the maximum operational effectiveness is obtained.

Description

technical field [0001] The invention belongs to the technical field of computer simulation and method optimization, and is mainly used for the distribution and scheduling problem of weapon resources carried on combat aircraft in cooperative air combat to targets. The technical method is also applicable to other distribution problems such as task distribution, vehicle scheduling, logistics transportation middle. Background technique [0002] The fire assignment problem, also known as the Weapon Target Assignment (WTA) problem, has been shown to be an NP-complete problem. The problem of coordinated air combat firepower distribution is to formulate a reasonable and efficient weapon-to-target distribution plan for the fighters in the formation, so as to determine which missile weapons on which combat aircraft will attack which enemy targets. At present, many scholars at home and abroad have carried out a lot of research on the problem of coordinated air combat firepower allocat...

AI Technical Summary

Problems solved by technology

If the distribution of the initial population is poor, for example, the frogs in the randomly generated initial frog population are likely to be concentrated in some local areas of the solution space, which will not only cause the algorithm to converge slowly, but also cause the algorithm to fall into a local optimum

In addition, the local search ability of the basic SFLA is poor, which makes the algorithm have the disadvantages of low solution accuracy and easy to fall into the local optimal extremum

In recent years, many scholars at home and abroad have done a lot of research on the improvement and application of SFLA, but most of the research is on single-objective optimization problems, and there are few researches on multi-objective optimization problems, and there is still no research on firepower optimization. Research literature on multi-objective leapfrog algorithm for assignment problems

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