Heuristics for noise-safe job-rotation problems considering learning-forgetting and boredom-induced job dissatisfaction effects

Pavinee Rerkjirattikal1,2,4, Tisana Wanwarn1, Stefano Starita3, Van-nam Huynh2,4, Thepchai Supnithi5, Sun Olapiriyakul1

1 School of Manufacturing Systems and Mechanical Engineering, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12121, Thailand
2 School of Knowledge Science, Japan Advance International Institute of Technology, Ishikawa 923-1211, Japan
3 Sasin School of Management, Chulalongkorn University, Bangkok 10330, Thailand
4 School of Knowledge Science, Japan Advance International Institute of Technology, Ishikawa 923-1211, Japan
5 Human Computer Communication Research Unit, National Electronics and Computer Technology Center, Pathum Thani 12121, Thailand

Abstract


In mitigating occupational hazards, there is often a need to use administrative controls such as job rotation over a prolonged period until the hazards can be eliminated or mitigated to safe levels. This research develops a noise-safe job-rotation optimization model that accounts for learning, forgetting, and boredom effects. Our analysis focuses on the case of human-paced and labor-intensive operations, considering the trade-off between safety and productivity. A case of multi-skilled workers that have heterogeneous skill levels with varying problem sizes is used to demonstrate the model s capabilities. A genetic algorithm and a randomized greedy algorithm are developed and shown to be effective in solving large-scale safe job rotation problems. Our results also show how the boredom and forgetting effects create productivity delays when job rotation is used.

Keywords


heuristics; job rotation scheduling; job satisfaction; learning-forgetting; occupational hazards

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