A GENETIC ALGORITHM-BASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES

The head nurse is generally responsible for creating work schedules for nurses in a nursing unit.However, since versatile constraints, shift requirements, and leave requests are imposed in theproblem, the generated schedule usually incurs complaints or criticisms from nurses on its impartiality.This study investigates a complex real nurse scheduling problem and constructs anoptimization model for the problem. The model consists of five minimization goals subject tofive hard constraints. Then a genetic algorithm-based optimization method is developed forsolving the optimization model. The method proposes a dedicated GA coding scheme for thesolution to this problem. Based on the scheme the method presents tailored crossover and mutationoperators for solution evolution. In the GA method, four selection operation modes areproposed to round in superior chromosomes for the next generation. A personnel data set from anursing unit of a real hospital is used in numerical tests. In addition, a modified hill climbinggreedy method and a well-performed variable depth search method from the literature are implementedto solve the same problem for numerical comparison. Numerical results suggest that adeterministic selection mode outperforms others and our method generates better schedules thanother methods on every run.