Abstract
In recent years, to alleviate the peak load of the power grid, many countries have implemented time-of-use (TOU) electricity tariffs. When both manpower and equipment are needed to perform project activities, wage and electricity costs become the main components of the total project cost. High-power activities can be implemented during off-peak periods to reduce energy costs and peak demand for electricity. Labor shift differential payments will increase wage costs for off-peak labor overtime. This paper proposes a bi-objective mixed-integer nonlinear programming model for resource-constrained project scheduling problems under TOU. Machine-level decisions are made to minimize total project cost and completion time. This model has an enormous solution space when there are many tasks and long durations, especially when the time granularity is small, which is not conducive to an accurate solution. Therefore, an improved NSGA-II algorithm is presented to effectively solve the model. The results show that the proposed model and algorithm can effectively reduce the total project cost and construction period while reducing peak power demand.
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Acknowledgments
This research was partly supported by the China Scholarship Council (grant number 201506455043), the National Natural Science Foundation of China (grant number 71501188), the Humanities and Social Sciences Planning Fund Project of the Ministry of Education of China (grant number 20YJA630022), and the Fundamental Research Funds for the Central Universities (grant number 19CX05026B).
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He, L., Zhang, Y. Bi-objective Optimization of RCPSP under Time-of-use Electricity Tariffs. KSCE J Civ Eng 26, 4971–4983 (2022). https://doi.org/10.1007/s12205-022-0095-4
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DOI: https://doi.org/10.1007/s12205-022-0095-4