Using a circadian rhythms model to identify optimal shift work schedules

With continuing evidence of the difficulties experienced by shift workers, much focus has been placed on designing shift schedules that minimize the adverse effects of shift work on human health and performance. One goal is the development of schedules that require workers to be on duty during the times they are most naturally alert. Chronobiologists have developed circadian rhythm based guidelines intended to aid in designing such shift work schedules. Some scientists have used these guidelines to develop automated scheduling tools and algorithms for the design of shift schedules that are less disruptive to a worker's innate rhythms. This research extends these empirical approaches by using a mathematical model of human circadian rhythms in evaluating existing schedules and developing optimal shift work schedules that minimize the disruption to a worker's natural rhythms.; Two differential equations models of human circadian rhythms developed by Kronauer et al. are modified to include the influence of shift work on the circadian system. Numerical simulations of sleep-wake rhythms corresponding to a variety of shift work schedules are compared with simulated free-run sleep-wake rhythms. The degree of deviation between the work-influenced rhythm and free-run rhythm serves as an indicator of how compatible a shift work schedule is with a worker's natural alertness level. Shift schedules that result in circadian rhythms closest to the free-run rhythms are identified as preferred schedules, and patterns within these schedules are noted.; The concept of using mathematical models to evaluate the degree of circadian disruption a specific shift schedule invokes is extended to allow for the development of “optimal” shift schedules. By parameterizing the shift work model, the process of finding an optimal shift schedule is reduced to solving a non-linear optimization problem. Two different circadian rhythms models are used in these studies to develop optimal one- and two-week shift schedules subject to a few assumptions about the shift schedules themselves. The results of these investigations are compared and optimal patterns and properties are identified.