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武器-目标分配问题(WTA)是联合作战中一个基本问题。针对WTA模型特点提出一种改进的遗传算法。该算法设计了新的编码策略,有效减少了模型的约束数目,并采用直接比较法处理约束,将问题转换成无约束优化问题。在遗传操作中设计了相应的组合混沌序列发生器,提高了种群质量,加快了收敛速度,结合二次插值法进行局部搜索提高了算法性能。数据实验结果表明该算法在可接受的时间内求得较高质量的解。
Weapons - Target Allocation (WTA) is a fundamental issue in joint operations. Aiming at the characteristics of WTA model, an improved genetic algorithm is proposed. The algorithm designed a new coding strategy, effectively reducing the number of constraints of the model, and using direct comparison method to deal with constraints, the problem is converted to unconstrained optimization problem. In the genetic operation, the corresponding combination chaotic sequence generator is designed to improve the quality of the population and speed up the convergence rate. Local search with quadratic interpolation method improves the performance of the algorithm. Data experimental results show that the algorithm can obtain a higher quality solution within an acceptable time.