【摘要】 针对工业洗涤设备多品种、小批量的生产特点，以最大加工时间最小化为目标，提出一种改进的遗传算法。对适应度函数进行改进，采用轮盘赌方式选择染色体，运用POX算子交叉法对染色体进行交叉操作，结合自适应调整的交叉概率与变异概率提高算法寻优能力与收敛速度。以作业车间调度问题标准算例FT06与LA01作为仿真实验对象，仿真结果表明，改进遗传算法的寻优能力与得到的最优解优于传统遗传算法，具有可行性与精确性。更多还原

【Abstract】 Aiming at the production characteristics of multiple varieties and small batches of industrial washing equipment, an improved genetic algorithm is proposed with the goal of minimizing the maximum processing time. It uses a roulette wheel to select chromosomes an improve the fitness function, applies the POX operator crossover method to perform crossover operations on chromosomes, and combines the adaptive adjustment of crossover probability and mutation probability to improve the algorithm’s optimization ability and convergence speed. Taking the standard examples FT06 and LA01 of the job shop scheduling problem as simulation experimental objects, the simulation results show that the improved genetic algorithm has better optimization ability and the obtained optimal solution than the traditional genetic algorithm, and is feasible and accurate.更多还原