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Site selection of construction waste recycling plant

机译:施工废物回收厂的选址

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摘要

Under the background of the development of construction waste recycling in China, optimizing the site of construction waste recycling and disposal plant is important, considering not only the cost of construction waste recycling but also the impact on the surrounding environment. This study aims to minimize the cost and negative environmental effects. In order to find the best method to solve the problem of multiobjective function optimization, we propose a multiobjective location model which combines genetic algorithm with probabilistic robust optimization. The model first uses genetic algorithm to get preliminary result and then it uses probabilistic robust optimization to find the optimal solution. The preliminary results show that 1, 3, 5 of the candidate sites more cost-effective and environmentally friendly than other. The fitness value converges at a stable value of 1.55 x 10(-5), and the Pareto optimal frontier presents considerable clustering characteristics, which prove the rationality and operability of the site selection optimization model. Meanwhile, the robust model analysis under the given uncertain environment achieves the purpose of further optimization of the site. The research results can provide the government with a theoretical basis for the site selection of construction and demolition waste recycling plants. (C) 2019 Elsevier Ltd. All rights reserved.
机译:在中国建筑废物回收的发展背景下,优化建筑废物回收和处理厂的遗址很重要,不仅考虑建筑废物回收的成本,而且考虑到周围环境的影响。本研究旨在最大限度地减少成本和负面的环境影响。为了找到解决多目标函数优化问题的最佳方法,我们提出了一种多目标位置模型,将遗传算法与概率稳健优化相结合。该模型首先使用遗传算法来获得初步结果,然后它使用概率强大优化来找到最佳解决方案。初步结果表明,候选地点的1,3,5比其他更具成本效益和环保。适应值在稳定值为1.55×10(-5)的情况下收敛,并且Pareto最佳前沿提供了相当大的聚类特征,这证明了站点选择优化模型的合理性和可操作性。同时,给定的不确定环境下的鲁棒模型分析达到了进一步优化现场的目的。研究成果可以为政府提供施工和拆迁废弃物植物的场地选择的理论依据。 (c)2019 Elsevier Ltd.保留所有权利。

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