Doctors Dynamic Scheduling For Outpatient, Inpatient, And Surgery Using Genetic Algorithm

Doctor scheduling and rescheduling play an essential factor in the day-to-day operation of the hospital. It is essential in scheduling suitable Doctors to provide the best service to patients with optimized resources. Rescheduling a doctor is unrecognized as an everyday time-consuming management task with different imperatives from scheduling. Poor rescheduling decisions can have quality, cost, and moral implications. This study aims to develop a genetic algorithm that can assist in scheduling and rescheduling doctors for medical resources. Our case study is classified as a re-planning problem using the genetic algorithm method in treating physician scheduling and rescheduling for outpatient, inpatient, and surgery. An integer permutation representation with 200 chromosomes is used, where each digit in the gene represents the work program. The crossover method used is Two-point crossover, reciprocal exchange mutation method, and elitism selection. The tests' results include a population size of 50 individuals with an average fitness of 0.4766667, 100 generations with an average fitness of 0.5, and the combination of Cr = 0.20 and Mr 0.80 with an average fitness of 0.48. the genetic algorithm can combine further research with a Hybrid Tabu Search Algorithm, Bee Colony Optimization Algorithm, and Harmony search algorithm (HSA) to produce an optimal schedule solution.