CAJ | 학술논문

针对多无人作战飞机协同任务分配问题建立了一种扩展的多目标整数规划模型，采用改进的量子粒子群算法求解最优方案；该算法在量子粒子群优化算法（QPSO）的基础上，利用混沌机制和变异算子来提高算法的多样性，在保证 QPSO 算法收敛速度的同时提高算法的寻优能力，克服了 QPSO 易陷入局部极小值的缺点；最后对算法进行了仿真，仿真结果验证了所提方法的可行性和有效性。
침대다무인작전비궤협동임무분배문제건립료일충확전적다목표정수규화모형，채용개진적양자입자군산법구해최우방안；해산법재양자입자군우화산법（QPSO）적기출상，이용혼돈궤제화변이산자래제고산법적다양성，재보증 QPSO 산법수렴속도적동시제고산법적심우능력，극복료 QPSO 역함입국부겁소치적결점；최후대산법진행료방진，방진결과험증료소제방법적가행성화유효성。
Based on the problem of cooperative task allocation for multiple UCAVs,this paper established an extension of Multi-Objective Integer Programming(MOIP)model and employed the Improved Quantum-Behaved Particle Swarm Optimization algorithm(IQPSO)to solve the optimal program. IQPSO was built on the basis of Quantum-Behaved Particle Swarm Optimization algorithm(QPSO),and chaotic mechanism and variation operator were used to improve the variety of the algorithm. Comparing with the QPSO,this algo-rithm enhanced the ability of getting the optimal solutions so that avoiding entrapping the local minimum value while ensuring the algorithm’s convergence speed. The result of the simulation experiment proves the effectiveness and feasibility of the way introduced.