中文摘要：

针对柔性作业车间调度问题,构建了以最大完工时间和总加工能耗最小为优化目标的多目标调度模型。发展了改进的混合蛙跳算法,通过设计基于MPX（Maximum Preserved Crossover）操作和单亲遗传算法基因移位操作的局部更新策略,避免了算法的非法解产生和修整,加快了算法寻优速率。并通过简化邻域寻优策略对组内最优解进行优化,防止算法陷入局部最优。通过求解某企业生产车间实例,得出了不同权重下的调度方案,并对比标准混合蛙跳算法下的最大完工时间和加工能耗,证明了算法的有效性。

英文摘要：

Aiming at the characteristics of flexible job shop scheduling problem, a multi-objective scheduling model with maximum completion time and minimum energy consumption was proposed. An improved shuffled frog leaping algorithm was developed. By designing the local updating strategy based on crossover operation of maximum preserved crossover （MPX） and shifting operation of single parent gene algorithm （PGA）, it avoided the illegal solution and trimming of the algorithm. Additionally, it accelerated optimization rate of the algorithm. And the optimal solution of the group was optimized by the simplified neighborhood optimization strategy to prevent the algorithm from falling into the local optimum. Then, by solving an example of an enterprise production workshop, scheduling schemes under different weights were obtained. Compared with completion time and processing energy consumption obtained by the classical shuffled frog-leaping algorithm, it proves the effectiveness of the algorithm.