Nursing 4.0 - artificial intelligence applied in automatic nurse rostering for healthcare organizations

• Grant number: 20/13392-8
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: January 01, 2022
• End date: December 31, 2022
• Field of knowledge: Health Sciences - Nursing - Public Health Nursing
• Principal Investigator: Thiago Franco
• Grantee: Thiago Franco
• Company: Thiago Franco
• CNAE: Consultoria em tecnologia da informação ; Pesquisa e desenvolvimento experimental em ciências físicas e naturais
• City: Ribeirão Preto
• Pesquisadores principais: André Luiz Teixeira Vinci
• Associated researchers: Renato Tinós
• Associated scholarship(s): 21/14776-7 - Nursing 4.0 - Artificial Intelligence applied in automatic nurse rostering for healthcare organizations., BP.TT; 21/14637-7 - Nursing 4.0: artificial intelligence applied in automatic nurse rostering for healthcare organizations, BP.PIPE

Abstract

Nurse rostering or scheduling is one of the most demanding tasks for managers. It demands in a single arrangement the balance of legal issues, union agreements, institutional rules, impositions from the nature of the work and needs of the team. It is a delicated and complex situation and due to this it is extremely necessary for the manager to have efficient assisting tools in the elaboration of this structure. Today, the vast majority of companies - regardless of size or area of activity - do not have any support tools to organize the work of their employees. Computationally speaking, in most cases, NRP is an NP-hard problem and due to its combinatorial nature, research in this domain is still a frontier of knowledge to be explored. In this project, we propose to investigate NRP by means of Genetic Algorithms, which have been used successfully for complex optimization problems. Key words: Nurse Rostering Problem (NRP), Genetic Algorithms, Optimization. (AU)