Development of a Multi-Skill Job Rotation Model by Minimizing the Workload Variance

Abstract

Performing risky or repetitive activities by the operator in each system causes some ergonomic dangers. To reduce these risks, employees must participate in such activities in equal amounts as much as possible. Evaluating this job and finding out how to allocate employees to various tasks during planning time is known as job rotation. In this paper, employees' shift work schedule and job rotation are investigated to reduce costs and consider This study aims to provide an optimal approach to the issue of shift work schedule and job rotation in which the main model is a nonlinear integer programming, and a genetic algorithm is used to solve the mathematical model. To examine the proposed model, the performance of the genetic algorithm is compared with the exact method (GAMS software). The results show that the performance of the genetic algorithm is better than the exact method in significant problems and requires lower computational time.