基于直觉模糊熵的改进粒子群算法求解WTA问题

doi:10.11896/j.issn.1002-137X.2016.12.046

摘要/Abstract

摘要： 为了提高求解武器目标分配问题的效率和性能,提出了一种基于直觉模糊熵的改进粒子群算法(IFEIPSO)。首先,针对WTA问题的多约束条件建立了整数编码方案,降低了问题的复杂性；其次,采用一种交换操作和模拟退火机制对粒子群算法的局部最优解进行更新,从而得到更优的局部最优解和全局最优解,以增加算法的局部搜索能力；最后,以直觉模糊熵作为种群多样性的测度,根据熵值大小对种群进行变异操作,提高种群的多样性,增加算法的全局搜索性能。仿真实验结果表明,该算法很好地提高了粒子群算法的寻优能力,有效地解决了WTA问题。

关键词: 武器目标分配,直觉模糊熵,交换操作,模拟退火机制,粒子群算法

Abstract: An improved particle swarm optimization algorithm for solving weapon- target assignment (WTA) problem based on intuitionistic fuzzy entropy (IFEIPSO) was proposed to improve the efficiency and performance.Firstly,the algorithm sets up an integer decoding scheme for a variety of constraints about WTA to decrease the complexity of problem.Then,the algorithm updates the partial best-solution of PSO by using an exchange operation and a simulated annealing mechanism which aims to get the better partial best-solution and global best-solution,and increases the partial searching ability.Finally,the algorithm uses a metric based on intuitionistic fuzzy entropy to measure the diversity of the population,and designs a mutation operation on the basis of entropy value to improve the population’s diversity and global searching performance.The results of simulation indicate that the algorithm improves the searching ability of PSO and it is useful for dealing with WTA problem.

Key words: Weapon-target assignment,Intuitionistic fuzzy entropy,Exchange operation,Simulated annealing mechanism,Particle swarm optimization

苏丁为,王毅,周创明. 基于直觉模糊熵的改进粒子群算法求解WTA问题[J]. 计算机科学, 2016, 43(12): 255-259. https://doi.org/10.11896/j.issn.1002-137X.2016.12.046

SU Ding-wei, WANG Yi and ZHOU Chuang-ming. Improved Particle Swarm Optimization Algorithm for Solving Weapon-target Assignment Problem Based on Intuitionistic Fuzzy Entropy[J]. Computer Science, 2016, 43(12): 255-259. https://doi.org/10.11896/j.issn.1002-137X.2016.12.046

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