Enhanced performance of overlap flow-shop scheduling involving reworking and a time buffer

This study presents an overlap scheduling solution to enhance system performance for branched-line flow-shop operations that involve reworking and a time buffer. In scheduling the branched-line operations involving reworking and a time buffer, two mutual inter-dependent problems must be solved: one is to determine the appropriate job schedule, and the other is to find a suitable time buffer at the right position of the system. Analysis results indicate that arranging a job sequence using a meta-search, of which the genetic algorithm-based best-fit search is the simplest, most effective, and least costly way for improving overlap flow-shop scheduling performance. In determining the job schedule involving reworking and a time buffer for branched-line operations, we propose a genetic algorithm-based overlap scheduling heuristic to perform the best-fit search using a pre-determined time buffer. Having found a suitable time buffer, we build a scheduling simulator to measure the performance for the job schedule that is determined by the genetic algorithm when a time buffer is added.