使用贪心模拟退火算法求解WTA问题

Using Greedy Simulated Annealing Algorithm to Solve WTA Problem

目的针对当前常用智能算法在求解武器-目标分配问题时存在的不足,将贪心算法思想融入模拟退火算法中,构建贪心模拟退火算法。方法贪心模拟退火算法的思想是基于模拟退火算法容易陷入局部最优解这一缺陷,将贪心思想融入模拟退火算法中,在每次模拟退火算法产生新解后对其进行局部贪心搜索,寻找到更优解,进而提高求解质量。结果分别使用相同的数据,采用遗传算法、神经网络算法以及贪心模拟退火算法对5个案例进行求解,均得到了最优解。结论贪心模拟退火算法的求解结果远远优于其他2种算法,证明了方法的有效性。

Objective Aimed at the shortcomings of current intelligent algorithms in solving weapon target assignment problem,the greedy algorithm idea is integrated into simulated annealing algorithm to construct greedy simulated annealing algorithm.Methods Based on the defect that the simulated annealing algorithm is easy to fall into the local optimal solution,the idea of greedy simulated annealing algorithm is to integrate greedy idea into simulated annealing algorithm.After each new solution,local greedy search is carried out to find more solutions and improve the solution quality.Results Genetic algorithm,neural network algorithm and greedy simulated annealing algorithm are used to solve five cases with same data,and the optimal solutions are obtained.Conclusion The greedy simulated annealing algorithm is much better than the two former algorithms,which proves the effectiveness of the method used in this paper.