A Python Based Approach to Minimize the Total Elapsed Time of Machines in Two Stage FSSM Including Job Block Criteria

This work introduces a straight forward Python method for reducing the total time taken in a two-stage flow shop scheduling problem, incorporating job block criteria. Johnson’s Rule is applied to determine the optimal sequence of jobs across two machines. The paper’s goal is to create an efficient algorithm, developed using Python, aimed at minimizing the overall time machines are in use while taking into account the job block criteria for specific jobs. To confirm the effectiveness of this method, a numerical example is provided.