Method for solving weapon target allocation problem based on cross entropy genetic algorithm

Abstract

The invention discloses a method for solving a weapon target allocation problem based on a cross entropy genetic algorithm. The method comprises the following steps: constructing a weapon target allocation discrete probability distribution matrix M and performing initialization; generating N samples meeting a weapon target allocation scheme solution; increasing the diversity of samples by using selection, crossover and mutation operations in a genetic algorithm; selecting H elite samples through fitness calculation; updating the discrete probability distribution matrix through an iterative formula of an optimal solution; and when an iteration termination condition is satisfied, outputting a final discrete probability distribution matrix which is an optimal solution. According to the method, the WTA problem existing in water surface ship formation combined air defense combat is solved through a data iteration optimization mode, and under the condition that the number of weapons of each ship is limited, ship air defense weapons are reasonably associated with incoming attacking targets, so that the air targets are intercepted, and the damage effect is maximized.

Description

technical field [0001] The invention relates to the field of military command and control auxiliary decision-making, in particular to a method for solving the weapon target allocation problem based on a cross-entropy genetic algorithm. Background technique [0002] The Weapon Target Assignment (WTA) problem is an important problem in the research of operational command assistant decision-making, and it is a kind of N-P complete problem. The key to the WTA problem is how to allocate weapons with different damage capabilities to targets with different attack posture threats, so as to achieve the maximum damage effect of the threat target. [0003] To solve the WTA problem, traditional numerical optimization algorithms, such as branch and bound method, enumeration method, gradient descent method, etc., are often not suitable for solving more complex WTA problems. At present, intelligent optimization algorithms are mainly used for solving. Liu Chuanbo et al. proposed a Memetic ...

AI Technical Summary

Problems solved by technology

Although there are many algorithms for solving SWTA problems, and some improvements have been made in terms of optimization accuracy, the algorithms are not satisfactory in terms of convergence speed and easy to fall into local optimal solutions, especially in the face of large-scale and complex problems. , there is still room for further improvement, so a method based on cross-entropy genetic algorithm to solve the problem of weapon target assignment is provided

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