Evolutionary Multi-Objective optimization for nurse scheduling problem

Nurse scheduling problem (NSP) is the problem of determining a reasonable and efficient work schedule for nurses. This paper presents a new external memory-based approach along with Multi-Objective Genetic Algorithms (MOGA) to solve multiobjective NSPs. In multiobjective modeling of NSPs, there are several objectives which are in conflict with each other, and there are some hard constraints that should be satisfied in any solution. The presented approach can solve multiobjective NSPs in an efficient way. As demonstrated by the experimental results, MOGA together with the maintained external memory extracted significantly more nondominated solutions compared to MOGA without a memory.