Surgical rescheduling problem with emergency patients considering participants’ dissatisfaction

Surgical rescheduling is necessary for adjusting initial schedules on surgery day after emergency demand is realized. While people-oriented medical service has been emphasized these years, the traditional rescheduling scheme which is only in pursuit of a great cost-related performance is no longer desirable since patients and medical staff are also highly involved in rescheduling and their preferences should not be ignored. In order to provide a satisfactory and people-centered rescheduling plan, this study considers the preferences of three involved participants (i.e. the operating room manager, medical staff, and elective patients) while designing a rescheduling plan. Based on prospect theory, we introduce three functions to evaluate three participants’ dissatisfaction about rescheduling schemes in terms of their respective preferences. Then a multi-objective rescheduling model is established with multiple resource constraints, emergency lead-time target constraints, and the objective of minimizing the dissatisfaction of three participants caused by rescheduling. A hybrid particle swarm optimization (HPSO) algorithm with two improved strategies—an initial population construction strategy and a local search strategy, is then developed to solve the proposed problem. Several numerical experiments are carried out by leveraging data reported in existing case studies in conjunction with simulated data. The results demonstrate the effectiveness of two improved strategies and show that the proposed HPSO algorithm can provide better Pareto solutions for our problem in comparison with the basic non-dominated sorting genetic algorithm.