Abstract
Maximizing Compressive strength and Minimizing the cost has always been the objectives for selection of mix design, but with the increase in recent interests in producing eco-friendly materials, another objective has been added to the above two, making it a complex multi-objective problem. This paper presents a way to solve this multi-objective optimizing problem in a more statistical way, optimizing concrete mix designs to obtain a high-strength, low carbon emission and economical mix design using recently developed nature-inspired algorithm namely Cuckoo Search (CS) algorithm. The algorithm was written in MATLAB and the results obtained consist of mix designs having strengths varying from 20 MPa to 90 MPa and their corresponding carbon emissions from 360 to 500 kg of CO2 Emissions for 1 m−3 of concrete. These results were compared with the results obtained with NSGAII and was concluded that MOCS performed better than NSGAII for this application producing wide spread pareto front.
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Boindala, S.P., Arunachalam, V. (2020). Concrete Mix Design Optimization Using a Multi-objective Cuckoo Search Algorithm. In: Pant, M., Sharma, T., Verma, O., Singla, R., Sikander, A. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 1053. Springer, Singapore. https://doi.org/10.1007/978-981-15-0751-9_11
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DOI: https://doi.org/10.1007/978-981-15-0751-9_11
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