A linear mathematical programming model for optimization of the energy consumption in construction projects

Document Type : Original Article

Authors

1 Faculty of Engineering, University of Garmsar, Garmsar, Iran

2 Department of Industrial Engineering, Razi University, Kermanshah, Iran.

10.22109/jemt.2021.250917.1259

Abstract

In this study, a linear mathematical programming model is formulated to manage the consumption of electrical energy and fossil fuels in the construction projects simultaneously. The aim is to determine at what time period and for how long each electric machine is employed in the whole project, the optimal number of periodic services for the machines with fossil fuels and optimal service time so that the total objective function value is minimized. The objective function of the proposed problem is the sum of electricity consumption costs, service costs and fossil fuel consumption costs in the whole project. In the proposed model, different intervals are considered for electrical energy consumption and the effects of the average speed of each machine with fossil fuel consumption and the time required to these machines in each day are also applied in decisions-making. For solving the mathematical model, the LINGO optimization software package is employed. For a better understanding of the behavior of the proposed problem, sample problems with different sizes are investigated and the results are interpreted graphically. The results show that the objective function value of the proposed problem increases with an increment in the project completion time and number of machines, the consumption cost of the fossil fuels machines accounts for a significant portion of the objective function value in all samples and also, the contribution of service costs is more than that of the electric machines. Also, the proposed model is implemented for a sample problem and its sensitivity to some parameters are tested. The results of sensitivity analysis show that by increasing the project completion time, the number of intervals selected for the daily use of electric machines, number of service times required for the fossil fuel machinery and consequently the amount of objective function are increased. Also, the model solving time increases logarithmically with an increment in the project completion time.

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