A Population-based Simulated Annealing Algorithm for Flexible J obshop Scheduling Problem with Lot streaming and A Parallel Assembly Stage

In this research a flexible job shop scheduling problem with a parallel assembly stage and Lot Streaming (LS) is studied. The objective function is to find a schedule which minimizes the makespan. First a mixed integer linear programming model is introduced to express ‘die problem and in order to demonstrate the accuracy of the presented model, some small instances are solved by GAMS. Due to the NP-hardness of the considered problem, a algorithm is used to solve the problem in medium to large sizes in reasonable amount of time. This algorithm is based on population based simulated annealing (PSA) algorithm. The results of ‘die proposed algorithm are compared with the result of simulated annealing algorithm. Computational results showed that for small problems, both PSA and SA have approximately the same performance. And in medium to large problems PSA outperforms SA. In addition, it is concluded that there is a direct relation between lot streaming technique and makespan time reduction.

A Population-based Simulated Annealing Algorithm for Flexible J obshop Scheduling Problem with Lot streaming and A Parallel Assembly Stage Keywords:

flexible job shop , parallel assembly , lot streaming , PSA