An approach to develop an effective job rotation schedule by using genetic algorithm

Job rotation is a significant approach of job design used in manufacturing, assembly or any service providing system, which requires the workers to move between different tasks, at fixed or irregular periods of time. Now a days it is increasingly employed in organizations because it benefits not only the workers by preventing musculoskeletal disorder, eliminating boredom and increasing job satisfaction but also the management by increasing productivity, creating morale and loyalty in workers and decreasing turnover rate. In this paper a job rotation schedule of a construction firm has been developed by using genetic algorithm to eliminate repetitive tasks for each of the workers. This genetic algorithm has been implemented as a multi-factor algorithm since it takes into account ergonomic, competence, environmental, and physical skill factors to develop an optimum job rotation schedule. Genetic operators-crossover and mutation are used to create new solutions in each generation maintaining some conditions. Finally a case study has been conducted to validate the proposed methodology.