A Hybrid Optimization Strategy About Nurse Scheduling Model Based On Integer Programming And Simulated Annealing Algorithm

Scientifically manage the medical resources, timely provide patients with quality serviceand can effectively control the budget are major issues which the nursing managers are facingtoday. The nursing resource management directly affects the quality and the cost of nursingcare. The rightful utilization and full exploitation of nursing resources has become the core ofmodern nursing care management. Due to hospitals bear the pressure to control costs, and thecurrent situation of a large number of nursing works, especially the strong emergency of thesework, and also the irregular shifts and the single, simple traditional scheduling mode, itresulted in some interest conflict and the differences of objectives between hospital and nurses.In order to improve the quality of nursing care service, reduce the cost of hospital nursingcare, I hope I can establish a complete issue model which has labor laws constraints and canmeet their own needs of nurses.-----This is one of the main purposes of this research.Nurse scheduling problem is the NP problem which is more difficult than the TSPproblem and it is part of the combinatorial optimization problem. On one hand, there are thedifficulties of highly computational complexity about the by using mathematicalprogramming; on the other hand, the heuristic algorithms reduce the solution search space,which easily fall into locally optimal solution. Therefore, I combined the advantages with thedisadvantages of the two algorithms, and then established a hybrid optimization strategybased on the branch and bound and simulated annealing (SA) algorithm, thus will effectivelyreducing the computational complexity and increase the solution search space.（1）From the perspective of feasibility and practicality of nursing care in hospital, Icombined it with the findings of Zhongshan XX Hospital Nurse Status Questionnaire, andsystematically explained the problem of nurse scheduling; Furthermore, it will increase theAPN scheduling mechanism, frequency discontinuous, weekend breaks and the fairness ofscheduling on the basis of basic ILP model, and establish a nurse scheduling model withstrong and soft constraints.（2）Introduce the branch and bound algorithm of Integer programming and simulatedannealing(SA), and finally design out a hybrid optimization strategy based on the branch ofthe integer programming and bound and simulated annealing(SA) algorithm,which take thefairness of scheduling frequency as the principle, as well as take advantage of the―NurseExchange Rules‖and the―Scheduling Frequency Adjustment Rules‖to generate newsolutions,and it then increase the search space probability of algorithm according toacceptance criteria. The experimental results show that nurse scheduling model with strong and softconstraints better consider the labor laws, scheduling frequency constraints, and the potentialdemand of nurses and some other factors. Most importantly, the quality of hybrid optimizationstrategy based on the branch and bound and simulated annealing (SA) algorithm solution isfar better than the mathematical programming and heuristic algorithms.