Abstract
The rapid urbanization in China over the last decade has resulted in increased carbon emissions from the construction materials industry. Considering significant proportion of material purchase in total project costs and the massive amount of carbon emissions during construction material produce and transportation process, the material supplier selection has significant influence on the construction performance. This paper develops an multi-objective equilibrium strategy based bi-level programming model which fully reflects the conflicts between the construction company and the material suppliers and considers the trade-off between cost optimization and carbon emission reduction. An interactive solution approach with fuzzy random variables is designed. A practical case is given to demonstrates the efficiency of the formulated method.
The original version of this chapter was revised: The affiliation of the authors Shuhua Hou and Rui Qiu has been updated. The correction to this chapter is available at https://doi.org/10.1007/978-3-030-21255-1_60
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20 June 2019
This paper develops an multi-objective equilibrium strategy based bi-level programming model which fully reflects the conflicts between the construction company and the material suppliers and considers the trade-off between cost optimization and carbon emission reduction. An interactive solution approach with fuzzy random variables is designed. A practical case is given to demonstrates the efficiency of the formulated method.
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Acknowledgement
This research has been supported by the project of Research Center for System Sciences and Enterprise Development (Grant No. Xq18B02) and Sichuan University (Grant No. 2018hhf-45).
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Sun, R., Hou, S., Qiu, R. (2020). A Multiple Decision-Maker Model for Construction Material Supply Problem Based on Costs-Carbon Equilibrium. In: Xu, J., Ahmed, S., Cooke, F., Duca, G. (eds) Proceedings of the Thirteenth International Conference on Management Science and Engineering Management. ICMSEM 2019. Advances in Intelligent Systems and Computing, vol 1002. Springer, Cham. https://doi.org/10.1007/978-3-030-21255-1_37
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DOI: https://doi.org/10.1007/978-3-030-21255-1_37
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