| With the development of modern defensive weapons, High energy laser weapons for its unique advantages has attracting the attention of many countries and has achieved great development. Modern air environment is often a multi-batch, multiple weapons coordination circumstance and put forward higher requirements to the Fire Command and Control System of modern defensive weapons.In this paper, two cases were in-depth discussed, one is assess threaten of multi-group targets, another is each batch contains multiple targets in the interception order issues. A multi-target laser anti-missile model was established by analysis the fly time, height, type and a shortcut of the incoming targets which affect the threat degree of target, we use the AHP and variable weights AHP to solve sort the threaten of multi-degree of target groups, the result as important basis for anti-Guided weapons priority to intercept targets.Laser anti-missile weapon interceptor multi-objective scheduling problem is essentially a dynamic TSP ( DTSP ) problem. In order to resolve the strategy optimization of laser weapon intercept multiple targets problem, this paper proposes an improved genetic algorithm and builds a reasonable model. It introduces the strategy of local search and keeps the best k individuals of the parent mechanism to the standard genetic algorithm. The computation with experimental data shows the improved GA greatly enhances the performance of the standard genetic algorithm, not only improves the precision of the algorithm, but also increases the stability and quicken the convergent speed of the algorithm. In order to resolve premature convergence of genetic algorithms, this paper proposes an improved niche genetic algorithm. Euclidean distance and the"bubble"distance were designed to measure the similarity of the permutations. Niche genetic algorithm combined with the punitive mechanisms improves"premature"phenomenon of the standard genetic algorithm. |
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