A hybrid meta-heuristic for the batching problem in just-in-time flow shops

This paper is concerned with a batching problem encountered in the context of production smoothing in just-in-time manufacturing systems. The manufacturing system of interest is a multi-level system with a flow-shop at the final level. We develop a hybrid meta-heuristic method to solve the batching problem, which is known to be NP-hard. We hybridize strategic oscillation (SO) and path re-linking (PR) methods and compare the hybrid method's performance to two benchmark methods: a bounded dynamic programming method developed for the problem earlier and an implementation of robust tabu search (RTS) meta-heuristic. Through a computational study, we show that the proposed hybrid method is effective in solving the problem within several minutes of computer time and yielding near-optimal results.