Flow shop scheduling including human factors impacting job processing times with learning and deterioration effects

Traditionally in scheduling problems, the job processing time is considered constant and for that, the throughput could be equal to the length of time, however, this simplification moves away from the real context. Human being usually represent variability and adds complexity when they are included into scheduling models, hence integrating scheduling theory and human factor means a represent a research opportunity. So, the aim of my research is to model and design optimization procedures to solve flow shop scheduling problems that consider human phenomena related to the learning and deterioration effect. So, the methodology suggested considers a systematic literature review to identify human characteristics, the objective functions related to phenomena previously mentioned, as well as approaches to model them. Afterwards, it will propose a model to integrate human characteristics considering economic and social criteria. Finally, solution methods will be built and applied to solve the problems. It is expected that results obtained can contribute to solving real problems in productive environments.