Tehran University of Medical Sciences Iranian Journal of Public Health 2251-6085 51 5 2022 05 08 1125 1133 Mashallah Torabi Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, Tehran, Iran 2. Central Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran Maryam Goodarzi 1. Central Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran 2. Technology Management Departments, Faculty of Management and Economy, Science and Research Branch, Islamic Azad University, Tehran, Iran Maryam Ahmadi Central Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran Hamideh Hamidi Central Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran Samira Elmi Central Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran Fatemeh Golmah Central Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran Samira Mortezaie Central Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran Parisa Nezari Central Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran 2020 08 02 2020 10 14 Background: Nurses play a key role in increasing the efficiency of healthcare systems. Given the 24-hour performance of hospitals and the small number of nurses in the field of treatment, it is quintessential to re-shift them in the hospital. This study set out to achieve coherence in nursing shift planning and justice in the order of shifts in hospital. Methods: This applied and a developmental study was performed from 2019 to 2020. We used genetic algorithm to provide operational solutions and define flexible shifts and plan nurses' working hours in Yas Hospital, Tehran University of Medical Sciences Hospital, Tehran, Iran. Results: Based on the selection of each nurse and determining the approved shifts of each ward, the possibility of appropriate planning was provided to determine the required shifts per month and to estimate the needs of each department. Conclusion: Using genetic algorithm and nursing shift in office automation console provides useful tools for managers at all organizational levels, according to which a good balance between the hospital's need for nurse and nurses’ demands in different time periods. https://ijph.tums.ac.ir/index.php/ijph/article/view/21673 https://ijph.tums.ac.ir/index.php/ijph/article/download/21673/7599