A Tabu Search-Based Heuristic for Single-Product Lot Streaming Problems in Flow Shops

Abstract

Lot streaming is a technique that splits a production lot consisting of identical items into sublots to improve the performance of a multistage production system by overlapping the sublots on successive machines. In this study, a single-product multistage stochastic flow shop problem with consistent sublot types and discrete sublot sizes is considered, and a heuristic algorithm which is a combination of simulation and tabu search is presented with the objective of minimizing makespan. First, the performance of the proposed heuristic is evaluated against a deterministic model, then it is applied to stochastic flow shops and the results are compared with those of Arena's OptQuest. The computational results show that the proposed heuristic gives rather efficient results and facilitates the solution of the considered complex stochastic lot streaming problems.