Genetic Algorithm for Hybrid Flow-Shop Scheduling with Parrel Batch Processors

In classical flow-shop scheduling problem, each processor can process one job at a time. However, in practice, there may be many processors that can process jobs batch by batch. We call these processors batch processors. If the processing time of a batch is equal to the largest processing time among its members, we call such a batch processor parallel batch processor. In this paper, we study the hybrid flow-shop problem in which the processors are parrel batch processors. This problem is obviously NP-hard. Therefore, we propose a genetic algorithm in this work.