Effects of NSGA-II Algorithm in Compare to Bee Colony Optimization on Nurse Scheduling Problem

Abstract

In this paper, a nurse scheduling problem in work shifts in a medical center and solving the model by Bee Colony Optimization (BCO) has been addressed. First, a multi-objective Mathematical model is presented in which nurses have been allocated based on different capabilities in a 30-day scheduling program considering the soft and hard constraints of the model. Then by reviewing the work regulations of nurses in hospitals of China, two sample problems have been designed and solved with the proposed algorithm. Also, in this paper, a comparison between the results of Bee Colony Optimization (BCO) algorithm and the Non-Dominated Sorting Genetic Algorithm (NSGA-II) has been made, and the results showed that bee colony optimization has a higher capability in discovering and searching in the more solutions infeasible area to find a better solution than the NSGA-II algorithm.