Human resources optimization in hospital emergency using the genetic algorithm approach
Arash Apornak, Sadigh Raissi, Abbas Keramati, Kaveh Khalili‐Damghani
Abstract
Human resource (HR) planning acts as an evaluating process staffing requirement for current and short-time future activities. This can be a complicated decision making process in an organization. It also requires responding to issues and taking action to close the gap between its current and future needs. The current research aimed to follow an evolutionary algorithm for such problem using the genetic algorithm (GA). During current research data gathered from a period of 36 months in a big hospital with 108 direct staffs of health care affairs. Here the fuzzy Delphi was applied to identify the influencing factors on the optimization of human resources. In order to minimize annual direct HR cost as well maximizing affaires, a composition fitness established. The proposed algorithm identified the number of specialist, general practitioners and nurses in three shifts after 500 of generations. The proposed plan promotes the fitness function about 36% and includes identifying the skills and abilities to encounter potential demand for emergency affairs.