多资源约束下改进NSGA-II算法的手术调度

针对手术调度涉及因素众多难以优化的问题, 在考虑手术台、执刀医师等资源约束,构建了以病人满意度及手 术总流程时间为目标函数的模糊调度数学模型. 针对传统的加权系数方法不能很好地解决手术多目标优 化问题,提出改进的非支配排序遗传算法(non-dominated sorting genetic algorithm II, NSGA-II),采用改进的拥挤密度排序法改善同一非劣等级内个体的排序; 提出自适应交叉和变异策略, 克服了种群早熟化,改善算法收敛速度; 采用改进精英策略保持种群多样性, 改善算法搜索性能. 最后, 将该算法应用于某三甲医院手术模糊调度中,仿真结果证明该方法的有效性和可行性.

Surgical operation scheduling with multi-resource constrained based on the improved NSGA-II algorithm

The optimization of operation scheduling is a tough work for many factors involved.To address it,a fuzzy scheduling model is presented with the object of a patient satisfaction and total operation time,which the operation platform,knife physicians and other resource constraints are covered.An improved non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ) is proposed in view of the traditional weighted coefficient method can not well address the problem of multi-objective optimization operation. The improved crowded density scheduling method is taken to improve the individual ranking within the non-inferior grade;a new adaptive crossover and mutation strategy is presented to avoid the population precocity and increase the convergence speed;the improved elite strategy is used to maintain the diversity of population and improve the algorithm performance.Finally,the algorithm is applied to an assigned hospital’s operation fuzzy scheduling,and the simulation results validate the feasibility and effectiveness of the method.