Bottleneck Identification in Resource-Constrained Project Scheduling via Constraint Relaxation
This work addresses the need for computer-assisted decision-making in production planning by reducing manual intervention, though it is incremental as it adapts existing approaches.
The paper tackles the problem of suboptimal schedules in resource-constrained project scheduling by automatically identifying bottlenecks and relaxing constraints to reduce tardiness, with methods showing comparable improvements between untargeted and targeted relaxations.
In realistic production scenarios, Advanced Planning and Scheduling (APS) tools often require manual intervention by production planners, as the system works with incomplete information, resulting in suboptimal schedules. Often, the preferable solution is not found just because of the too-restrictive constraints specifying the optimization problem, representing bottlenecks in the schedule. To provide computer-assisted support for decision-making, we aim to automatically identify bottlenecks in the given schedule while linking them to the particular constraints to be relaxed. In this work, we address the problem of reducing the tardiness of a particular project in an obtained schedule in the resource-constrained project scheduling problem by relaxing constraints related to identified bottlenecks. We develop two methods for this purpose. The first method adapts existing approaches from the job shop literature and utilizes them for so-called untargeted relaxations. The second method identifies potential improvements in relaxed versions of the problem and proposes targeted relaxations. Surprisingly, the untargeted relaxations result in improvements comparable to the targeted relaxations.