Flexible personnel scheduling in large multi-product unpaced asynchronous assembly lines

Employees are one of the effective factors in increasing productivity. The efficiency and effectiveness of employees increase with increased job satisfaction. Considering the priorities of employees in work environments is one of the factors of job satisfaction. This research presents a new multi-objective nonlinear mixed-integer scheduling model for staff scheduling in large un-paced asynchronous assembly lines. In this model, production planning is independent of the impact of human resource management. This model considers the competencies and priorities of each employee and the competency requirements required to assign each employee to the assembly activities. Each employee has four options: the duration of the shift, assembly activities, the number of transitions between assembly activities at different stations, and the start time of each break. This model aims to allocate employees to assembly activities while minimizing operating costs and employee dissatisfaction. For validating the model, a small problem with theoretical data solves by CPLEX. Due to personnel scheduling problems are NP-Hard. Solution times of exact approaches are high, which is not acceptable even for small problems. By considering large assembly lines with many personnel and requiring solutions in short and fast times and indicating that this proposed model is applicable, this model should be solved by Meta-heuristic methods so that the results show the efficiency of this model.