Real-world manufacturing scenarios usually lead to difficult assembly scheduling problems. Besides strict precedence constraints between jobs or operations, such problems incorporate constraints related to maintenance activities on working stations (machines) and specific setup times when different operations are executed on the same machine. This paper analyzes the performance of several approaches, based on mathematical programming and on (meta)heuristics, to solve flexible assembly scheduling problems characterized by an arbitrary tree-like structure of the operation network. In this context, a specific encoding of candidate solutions and some specific perturbation operators are proposed. The encoding and the operators allows the distribution of sub(batches) of operations on several machines which leads, for some assembly scheduling problems, to a significant decrease of the makespan.
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