This work presents efficient algorithms based on Mixed-Integer Linear Programming (MILP) for complex job-shop scheduling problems raised in Automated Manufacturing Systems. The aim of this work is to find alternative solution approaches of production and transportation operations in a multi-product multistage production process that can be used to solve industrial-scale problems with reasonable computational effort. The MILP model developed must take into account; dissimilar recipes, single unit per production stage, re-entrant flows, sequence- dependent free transferring times and load transfer movements in a single automated material-handling device. In addition, logical-based strategies are proposed to iteratively find and improve the solutions generated over time. These approaches were tested in different real-world problems appeared in the surfacetreatment process of metal components in aircraft manufacturing industry.Sociedad Argentina de Informática e Investigación Operativ
