CAJ | 학술논문

装配生产线上螺母紧固优化路径属于多项式复杂程度的非确定性问题，即NP ( non-deterministic polynomial)完全问题，由于该问题的时间复杂度随着问题规模的增大按指数方式增长，到目前为止还未找到一个有效的多项式时间算法，对机械手的运行路径进行优化。针对该问题，引入逆转算子对遗传算法进行改进，进而对机械手的运行路径优化问题进行了深入研究，并对螺母紧固优化路径进行了MATLAB仿真对比研究，仿真结果表明该改进遗传算法能很好的跳出局部极小值，并能快速、稳定的寻找到最优值。
장배생산선상라모긴고우화로경속우다항식복잡정도적비학정성문제，즉NP ( non-deterministic polynomial)완전문제，유우해문제적시간복잡도수착문제규모적증대안지수방식증장，도목전위지환미조도일개유효적다항식시간산법，대궤계수적운행로경진행우화。침대해문제，인입역전산자대유전산법진행개진，진이대궤계수적운행로경우화문제진행료심입연구，병대라모긴고우화로경진행료MATLAB방진대비연구，방진결과표명해개진유전산법능흔호적도출국부겁소치，병능쾌속、은정적심조도최우치。
Optimization path of tightening nut on the assembly line is a non-deterministic polynomial complexity problem, the NP ( Non-deterministic Polynomial) complete problem. Because the time complexity of the problem increases with the size of the prob-lem exponential y, an efficient polynomial-time algorithm is not found to optimize the robot running path by now.For this, this article introduces reversed operator into improving the genetic algorithm and deeply making a study of the optimization of the running path, for the manipulators, and the MATLAB simulation of the nut tightening path. The simulation results indicate that the improved genetic algorithm can be used to step over the local minimum, and find the optimal values fastly and stably.