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Bi-objective Optimization of RCPSP under Time-of-use Electricity Tariffs
https://orcid.org/http://orcid.org/0000-0001-7535-9542
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.
Bi-objective Optimization of RCPSP under Time-of-use Electricity Tariffs
https://orcid.org/http://orcid.org/0000-0001-7535-9542
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.
Bi-objective Optimization of RCPSP under Time-of-use Electricity Tariffs
https://orcid.org/http://orcid.org/0000-0001-7535-9542
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.
Bi-objective Optimization of RCPSP under Time-of-use Electricity Tariffs
KSCE J Civ Eng
He, Lihua (author) / Zhang, Yajun (author)
KSCE Journal of Civil Engineering ; 26 ; 4971-4983
2022-12-01
13 pages
Article (Journal)
Electronic Resource
English
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