Abstract: A multi-objective scheduling method for batch production flexible job shop scheduling problem (FJSP) under mixed work calendars was proposed. Considering the constraints of mixed work calendars of equipment, a multi-objective scheduling model for batch production FJSP with the objectives to minimize production cycle and manufacturing cost were designed. An elitist non-dominated sorting genetic algorithm (NSGA II) was designed to solve the researched model. A two-segment encoding method based on processes and equipment was used to respectively encode the processes and equipment. A two-segment crossover and mutation operator based on processes and equipment was used to implement crossover and mutation operation, in which an improved strategy of genetic operators was applied to ensure feasibility of the progeny individuals. In decoding operation, the principle based on parallel and sequence shift mode, and the time reckoning technology based on each equipment's calendar were used to calculate the begin and end time of each adjustment and process. Finally, effectiveness of the proposed method was validated by case study.

Key words: batch production flexible job shop scheduling problem, multi-objective optimization, mixed work calendars, parallel and sequence shift mode, NSGA II