南京航空航天大学学报（英文版）2006，Vol.23Issue(1)：20-26,7.
协同多目标攻击空战决策的启发式粒子群优化算法
HEURISTIC PARTICLE SWARM OPTIMIZATION ALGORITHM FOR AIR COMBAT DECISION-MAKING ON CMTA
摘要
Abstract
Combining the heuristic algorithm (HA) developed based on the specific knowledge of the cooperative multiple target attack (CMTA) tactics and the particle swarm optimization (PSO), a heuristic particle swarm optimization (HPSO) algorithm is proposed to solve the decision-making (DM) problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts (FAs) to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA-based algorithms in searching for the best solution to the DM problem.关键词
空战决策/协同多目标攻击/粒子群优化法/启发式算法Key words
air combat decision-making/cooperative multiple target attack/particle swarm optimization/heuristic algorithm分类
航空航天引用本文复制引用
罗德林,杨忠,段海滨,吴在桂,沈春林..协同多目标攻击空战决策的启发式粒子群优化算法[J].南京航空航天大学学报（英文版）,2006,23(1):20-26,7.基金项目
航空科学基金(02F15001)资助项目. （02F15001）
