CAJ | 학술논문

考虑蚁群算法与粒子群算法的各自特点,在粒子群算法的基础上借鉴蚁群算法的信息素机制,对粒子群算法的速度位置更新公式重新定义,提出了一种基于蚁群混沌行为的离散粒子群算法,并将其应用到背包问题中.实验结果表明,该算法可以得到较优解.
고필의군산법여입자군산법적각자특점,재입자군산법적기출상차감의군산법적신식소궤제,대입자군산법적속도위치경신공식중신정의,제출료일충기우의군혼돈행위적리산입자군산법,병장기응용도배포문제중.실험결과표명,해산법가이득도교우해.
Considering their own characteristics of ant colony algorithm and particle swarm optimization algorithm,the update equations of the speed and position of particles were redefined on the basis of PSO algorithm.A discrete particle swarm optimization algorithm based on chaotic ant behavior was proposed using the idea of pheromone refresh mechanism of ant colony algorithm for reference.Knapsack problem was used to test the performance of the algorithm.Compared with other algorithms,the results of the experiment show that the proposed algorithm can result in better profits.