Mitigation of health and safety risks to employees at remote locations through shift scheduling

The fly-in fly-out (FIFO) system is typical in remote mineral, oil, and energy operations, where employees work on-site for 2-3 weeks followed by an equal period at home. This schedule, involving shifts of 8, 10, or 12 hours, often leads to mental health, economic, and social impacts. This paper introduces an optimization model to address the atypical scheduling problem of two 12-hour shifts with unequal numbers of employees. Formulated as a mixed-integer non-linear model, the objective is to minimize the relative risks associated with night shifts. The model ensures an even distribution of night shifts among the team throughout the year, reducing night shifts to 6 hours per day with at least 6 hours of rest before and after a given nighttime work shift, implementing serial sleeping, and limiting cumulative night shift hours to less than 56 per month. Two case studies were carried out. The first case is a one-shot and solved by AMPL. The second case is a consecutive description and solved by an intelligent algorithm due to the size of the problem. Compared to the current schedule in the practice of working 14x12h=168h/m night hours, as well as to the benchmark/threshold 8x8h=64h/m night hours, the new schedule presents less risk to employees and by extension, to the operation by limiting the night-time working hours. This model improves workforce efficiency, safety, work quality, and can lead to financial savings for companies by distributing night shifts evenly among team members and avoiding permanent or block assignments.