A two-phase genetic algorithm to solve variants of the batch sequencing problem

We introduce the batch sequencing problem with item and batch availability for the single machine and two machine flow-shop case. We propose a genetic algorithm which solves all variants through a decomposition of the problem into a Phase I-Batching and a Phase II-Scheduling decision. The batch sequencing problem is closely related to the discrete lotsizing and scheduling problem (DLSP). Computational experience shows that our algorithm favourably compares with procedures for the DLSP.