Abstract: 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.

Key words: flexible job shop scheduling, shuffled frog-leaping algorithm, multi-objective optimization, energy consumption