This work presents efficient algorithms based on Mixed-Integer Linear Programming (MILP) and heuristic strategies for complex job-shop scheduling problems raised in Automated Manufacturing Systems. The aim of this work is to find alternative a solution approach of production and transportation operations in a multi-product multi-stage production system that can be used to solve industrial-scale problems with a reasonable computational effort. The MILP model developed must take into account; heterogeneous recipes, single unit per stage, possible recycle flows, sequence-dependent free transferring times and load transfer movements in a single automated material-handling device. In addition, heuristic-based strategies are proposed to iteratively find and improve the solutions generated over time. These approaches were tested in different real-world problems arising in the surface-treatment process of metal components in the aircraft manufacturing industry.Fil: Aguirre, Adrian Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Nordeste; ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Nordeste; ArgentinaFil: García Sanchez, Alvaro. Universidad Politecnica de Madrid; EspañaFil: Ortega Mier, Miguel. Universidad Politecnica de Madrid; Españ
