Solution of a flexible jobshop scheduling problem using an Estimation of Distribution Algorithm

The flexible jobshop scheduling problem permits the operation of each job to be processed by more than one machine. The configuration mentioned generally seeks to minimize the completion time of all jobs known in the literature as 'makespan'. We propose an Estimation of Distribution Algorithm for Sequencing, AEDS for simplicity and functionality. The AEDS attempts to find a relationship or interaction between the input variables, jobs, operations and shifts to optimize the output variable of real manufacturing processes, the makespan. In this sense the AEDS algorithm is used to guide the search and to solve the problem. In the algorithm, three graphical models were used to find better solutions. To set off-duty hours for operators before starting their activities in each shift as an input parameter and its development through the AEDS algorithm is a novelty of this research on the current research work. The comparison between AEDS and a genetic algorithm shows the effectiveness of AEDS solving the problem statement. Using the AEDS proposed, the performance Of real manufacturing processes can be improved significantly when different machines are assigned to different schedules.