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• W3169487746 abstract "This study focuses on staff scheduling problems in a natural gas combined cycle power plants with demanding shift systems. Scheduling the personnel working in power plants to the most suitable shift program can be arduous in terms of energy supply security. Natural gas combined cycle power plants are labor units where an expensive resource such as labor is used intensively. The primary aim in these types of enterprises is to ensure maximum employee satisfaction with minimum operating and labor costs. To meet this goal, companies must use various techniques. Shift scheduling models can also be considered as one of the useful tools in this respect. A constraint programming model has been developed for the shift scheduling problem. This model allows personnel to be assigned equally to shifts, minimizing the cost increase due to overtime. The proposed model satisfies the need for electricity generation in a big natural gas combined cycle power plant was operated in Turkey with real data has an acceptable calculation time to obtain the optimal solution. Staff scheduling model with the proposed improvements to the problem is provided close to 33% compared with the present situation. The calculation results show that the constraint programming model gives better results than the current schedule. The specificity of this study can be listed as follows: Firstly; the different model is presented in detail for the personnel scheduling problem, compared with the actual results and the results of the proposed model. Secondly, the personnel scheduling problem is modelled as a task-source match with the standard scheduling logic and modelled effectively with constraint programming. With the model, suitable solutions can be produced in a short time calculation period." @default.
• W3169487746 created "2021-06-22" @default.
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• W3169487746 date "2021-12-01" @default.
• W3169487746 modified "2023-10-18" @default.
• W3169487746 title "Shift scheduling solution with hybrid approach in a power plant" @default.
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• W3169487746 doi "https://doi.org/10.1016/j.aej.2021.03.076" @default.
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