Research On The Modeling And Algorithms For Elective Surgery Planning And Scheduling Problems

With the reformation of the health care system in progress, the community has paid increasing attention to medical service industry. The operating department is the nuclear part of hospital, its service quality influences patients’body health even life. The managers of hospital have paid much attention to service quality. The meaning of this research can be described as follows:Firstly, to decrease the risk of illness deterioration through optimizing time arrangement, decreasing each patient’s waiting time. Secondly, to prevent the operation accident caused by being over fatigue through optimizing each surgeon’s workload. Above all, this paper focuses on optimizing surgery arrangement, building a reasonable, harmonious surgery environment. Surgery planning and scheduling problem can be defined as two levels, to assign the surgery time and operating location on the planned level and to schedule the operating sequence on the scheduling level, which has plagued the staff in the operating theater for a long time, becoming the bottleneck of the department. This paper focuses on three issues as follows.The first issue is to solve patient-priority-based elective surgery planning problem. It focuses on partitioning patients into different priorities according to the state of illness. An optimization model with the aim of maximizing customer satisfaction is established under the consideration of a three-dimensional parameter constraint related patients, operating rooms and medical staffs. A genetic algorithm and heuristic based on patient priority algorithm are proposed to solve this issue.The second issue is to solve surgical scheduling problem under the consideration of government policy, which named the classification management of operating rooms. The organizational structure of hospital is taken into account during the process of modeling. A planned model and a scheduled model are built under the consideration of patients, operating rooms and surgeons constraints. A two-stage no-wait surgical scheduling heuristic algorithm (TNSS) is developed for scheduling. Combined TNSS with the classic rule FCFS, SPT, LPT and discrete PSO, F-TNSS, S-TNSS, L-TNSS and DPSO-TNSS algorithm are formed to solve surgical scheduling problem. The character of algorithms is analyzed under different constraint value and data scale. The third issue is to solve multiple-objective surgical scheduling problem. Three-point time estimation method is used to forecast the variance and mean value of operating length of each patient. A model is established with multiple objectives that to minimize the surgical operating delay risk and to minimize the illness deterioration risk. The influence of variance and mean value on the objective is analyzed on the issue. Because PSO algorithm has a character of convergence quickly, MOPSO is chose to solve the problem. discrete PSO is transformed to continuous PSO under the coding policy. The performance of the algorithm is analyzed under different value of parameters.