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University of Belgrade - Faculty of Civil Engineering , Belgrade , Serbia
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University of Belgrade - Faculty of Civil Engineering , Belgrade , Serbia
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University of Belgrade - Faculty of Civil Engineering , Belgrade , Serbia
Faculty of Civil Engineering, University of Belgrade , Belgrade , Serbia
This paper presents a hybrid model integrating the Analytic Hierarchy Process (AHP) and Genetic Algorithms (GA) to optimize construction machinery selection based on cost, CO2 emissions, maintenance, and age. AHP was used to determine precise weighting criteria, while a Python-based GA explored the solution space using technical penalty functions. Results demonstrate the model's efficiency in balancing fleet performance and costs. The proposed model enables unbiased decision-making, significantly reducing subjectivity in engineering judgment and providing an objective framework for sustainable resource management.
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