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Strengthening the PSO algorithm with a new technique inspired by the golf game and solving the complex engineering problem
Complex & Intelligent Systems ( IF 5.8 ) Pub Date : 2021-02-17 , DOI: 10.1007/s40747-021-00292-2
Serkan Dereli , Raşit Köker

This study has been inspired by golf ball movements during the game to improve particle swarm optimization. Because, all movements from the first to the last move of the golf ball are the moves made by the player to win the game. Winning this game is also a result of successful implementation of the desired moves. Therefore, the movements of the golf ball are also an optimization, and this has a meaning in the scientific world. In this sense, the movements of the particles in the PSO algorithm have been associated with the movements of the golf ball in the game. Thus, the velocities of the particles have converted to parabolically descending structure as they approach the target. Based on this feature, this meta-heuristic technique is called RDV (random descending velocity) IW PSO. In this way, the result obtained is improved thousands of times with very small movements. For the application of the proposed new technique, the inverse kinematics calculation of the 7-joint robot arm has been performed and the obtained results have been compared with the traditional PSO, some IW techniques, artificial bee colony, firefly algorithm and quantum PSO.



中文翻译:

利用高尔夫运动启发的新技术并解决复杂的工程问题来增强PSO算法

这项研究是受比赛中高尔夫球运动的启发,以改善粒子群优化。因为,从高尔夫球的第一动作到最后动作的所有动作都是玩家为赢得比赛而进行的动作。赢得这场比赛也是成功实施期望动作的结果。因此,高尔夫球的运动也是最优化的,这在科学界具有意义。从这个意义上讲,PSO算法中的粒子运动已经与游戏中高尔夫球的运动相关联。因此,当粒子接近目标时,它们的速度已转变为抛物线下降的结构。基于此功能,这种元启发式技术称为RDV(随机下降速度)IW PSO。这样,只需很小的运动,结果就可以提高数千倍。为了应用该新技术,对7关节机器人手臂进行了逆运动学计算,并将所得结果与传统PSO,一些IW技术,人工蜂群,萤火虫算法和量子PSO进行了比较。

更新日期:2021-02-17
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