a novel decision support system for discrete cost-co2 emission trade-off in construction projects: the usage of imitate genetic algorithm

نویسندگان

محمد علی بهشتی نیا

استادیار گروه صنایع، دانشکدۀ مواد و صنایع، دانشگاه سمنان، ایران ناهید فرازمند

دانشجوی کارشناسی ارشد mba، دانشکدۀ مواد و صنایع، دانشگاه سمنان، ایران

چکیده

under an intensive competitive environment, the construction industry is facing pressure to meet the higher customer expectations under a tighter budget. on the other hand, construction is one of the main sectors generating greenhouse gases. according to published statistics, construction industry is one of the most important resources of greenhouse emissions in the world. therefore, based on the growing attention to the environment situation and according to the enabler capabilities of the decision support systems, in this paper, a genetic algorithm-based decision support system for solving a trade-off problem between the cost and the amount of co2 emissions in construction projects is proposed. the genetic algorithm proposing here, is the new algorithm, named “imitate genetic algorithm”. for showing the reliability of the proposed algorithm, the results of its application have been compared with the results of classic genetic algorithm for 108 problems with different sizes. the results show the excellence of the proposed algorithm in comparison with classic genetic algorithm.

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