Abstract

The decisions on the strategic and tactical level contained in the operation room scheduling process are based on the expected demand. This demand is used to construct the master surgery schedule in a block booking system, which serves as a base for the planning and scheduling of surgical cases. However, in the operational phase, the actual demand may differ from the expected demand. This leads to increased waiting times, the cancellation of surgical cases and an inefficient utilisation of the operation room department for surgeons with spare capacity. In this paper, we study the Surgical Case re-Planning and Scheduling problem with resource re-scheduling that arises at block release time where the operation room planner tries to balance the capacity and the demand on the operational level. To that purpose, changes with respect to the surgeon schedule and the nurse roster are considered to adequately re-plan and schedule surgical cases. The problem under study minimises the number of changes related to the patient planning, the patient waiting time and the resource re-scheduling cost. We propose a three-phase heuristic that uses column generation to construct a high-quality feasible solution, which is further improved via local branching. Computational experiments have been conducted on an artificial dataset generated in a controlled and structured manner and on real-life data. Results demonstrate that our approach is able to produce (near-)optimal solutions and show the contribution of the different algorithmic building blocks.

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