Optimization model for selecting optimal prefabricated column design considering environmental impacts and costs using genetic algorithm

Abstract

Prefabricated columns are commonly used in construction projects due to their advantages, such as high quality, fast construction, environmental friendliness, and cost-effectiveness. Toward achieving the minimization of environmental impacts and costs through the prefabricated system at the same time, the optimal design should be conducted during the pre-construction phases. Therefore, this research aims to develop an optimization model that uses a genetic algorithm to select optimal prefabricated column designs considering both environmental impacts and costs. This study was conducted in four steps: (i) Data collection, (ii) Calculation of environmental impacts, (iii) Economic assessment, and (iv) Optimization using a genetic algorithm. The results showed that the average environmental impacts for global warming potential (GWP), ozone layer depletion potential (ODP), acidification potential (AP), eutrophication potential (EP), photochemical ozone creation potential (POCP), and abiotic depletion potential (ADP), were 8382.10 kg-CO2, 1.76 × 10−4 kg-CFC-11, 11.03 kg-SO2, 1.89 kg-PO43-, 6.94 kg-C2H4, and 47.60 kg-sb, respectively, with an integrated value of $177.14. The average total cost of the prefabricated column was $4591.17. The overall environmental impacts and costs of the prefabricated columns were $26,020.37 and $680,477.36, respectively, whereas the optimal columns were $19,219.56 and $492,708.32, representing reductions of 26.14% and 27.59%, respectively. The implications of this research are of great importance for sustainable construction practices, as it provides a practical framework for selecting optimal prefabricated column designs that simultaneously minimize environmental impacts and costs. The integration of genetic algorithms within the optimization model enables the identification of environmentally friendly and cost-effective solutions, contributing to the overall reduction of environmental impacts associated with construction activities.