| Resumo: | An important scheduling function of manufacturing systems is controlled order release. While there exists a broad literature on order release, reported release procedures typically use simple sequencing rules and greedy heuristics to determine which jobs to select for release. While this is appealing due to its simplicity, its adequateness has recently been questioned. In response, this study uses an integer linear programming model to select orders for release to the shop floor. Using simulation, we show that optimisation has the potential to improve performance compared to ‘classical’ release based on pool sequencing rules. However, in order to also outperform more powerful pool sequencing rules, load balancing and timing must be considered at release. Existing optimisation-based release methods emphasise load balancing in periods when jobs are on time. In line with recent advances in Workload Control theory, we show that a better percentage tardy performance can be achieved by only emphasising load balancing when many jobs are urgent. However, counterintuitively, emphasising urgency in underload periods leads to higher mean tardiness. Compared to previous literature we further highlight that continuous optimisation-based release outperforms periodic optimisation-based release. This has important implications on how optimised-based release should be designed.
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