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Optimal workforce size determination for workload management activities plays an important role in manufacturing systems. Still, the workload distribution problem is a challenging task under multi-objective considerations. This paper proposes a nonlinear multi-objective workload optimisation approach for maintenance systems. The proposed model considered the effects of workers’ absenteeism and accident severity factors on workforce effectiveness and productivity. Consideration is given to conflicting workforce objectives with stochastic and deterministic workforce constraints using a genetic algorithm (GA) as a solution method. The performance of the proposed model is compared with an existing workforce model. GA and particle swarm optimisation (PSO) results are compared on the basis of their performance using the proposed model. It is observed that our model performs better than the existing model. The …