Multistage operating room sequencing problem
This data is about a specific problem in surgery scheduling that focuses on dividing surgeries into different phases to improve resource scheduling. The problem is based on real-life situations in a private hospital in Belgium and involves sequencing surgeries and determining their start times, taking into account the availability of various resources such as rooms, surgeons, and anesthesiologists. The main goal is to efficiently allocate and use resources to minimize the number of overtime hours they are engaged. The approach includes dividing the peri-operative stage into different phases, each requiring a specific mix of resources, which differs from traditional approaches that assign resources for the entire surgery duration. This flexibility helps create a more efficient schedule by reducing resource idle time and associated costs. The dataset consists of two parts. The first part, named "General", is synthetic data meticulously generated to simulate real-life environments, validating the stability and efficiency of the proposed algorithm. The second part, named "Reallife" involves a case study conducted at the private hospital Sint-Elisabeth Zottegem (Belgium) to assess the value of dividing surgeries into multiple resource phases. To gather the necessary instance information, we conducted interviews with key personnel responsible for composing OR schedules and examined the OR logbook for July 2022. This resulted in the collection of data for 20 instances, with each instance representing the activities of a single day and the total number of patients ranging from 38 to 88. This dataset is designed to consider resource assignment to, dismissal from, and return to surgical cases at different stages (pre-surgery, peri-surgery, post-surgery, recovery, etc.). The findings of this research are detailed in the paper titled "A Two-Layer Heuristic for Patient Sequencing in the Operating Room Theatre Considering Multiple Resource Phases," currently under review. Further information, including the DOI, will be assigned upon acceptance. It's worth noting that the paper under review explores a problem similar to others, such as the work by Latorre-Núñez et al. (2016) on scheduling operating rooms with consideration of all resources, post-anesthesia beds, and emergency surgeries (Computers & Industrial Engineering, 97, 248-257). Some notes: 1- Each folder contains a subfolder called "Instance" which includes all instances in HTML format. The information is organized in an object-oriented manner using related tag objects. 2- Other subfolders include the result and solution for each instance in HTML format. For example, the subfolder "MIP" includes all solutions reported by CPLEX from the MIP model under a 3600-second time limit. For more information about the model and PC, please refer to the linked paper. 3- All files have a "description" tag that provides a brief summary of their contents.