Designing safe job rotation schedules using optimization and heuristic search

Abstract

Job rotation is one method that is sometimes used to reduce exposure to strenuous materials handling; however, developing effective rotation schedules can be complex in even moderate sized facilities. The purpose of this research is to develop methods of incorporating safety criteria into scheduling algorithms to produce job rotation schedules that reduce the potential for injury. Integer programming and a genetic algorithm were used to construct job rotation schedules. Schedules were comprised of lifting tasks whose potential for causing injury was assessed with the Job Severity Index. Each method was used to design four job rotation schedules that met specified safety criteria in a working environment where the object weight, horizontal distance and repetition rate varied over time. Each rotation was assigned to a specific gender/lifting capacity group. Five versions of the integer programming search method were applied to this problem. Each version generated one job rotation schedule. The genetic algorithm model was able to create a population of 437 feasible solutions to the rotation problem. Utilizing cluster analysis, a rule set was derived from the genetic algorithm generated solutions. These rules provided guidelines for designing safe job rotation schedules without the use of a computer. The advantages and limitations of these approaches in developing administrative controls for the prevention of back injury are discussed.