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Site selection of construction waste recycling plant

机译:建筑垃圾回收厂的选址

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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:在中国建筑垃圾回收发展的背景下,优化建筑垃圾回收处置场的位置非常重要,不仅要考虑建筑垃圾回收的成本,还要考虑对环境的影响。这项研究旨在最小化成本和负面环境影响。为了找到解决多目标函数优化问题的最佳方法,我们提出了一种结合遗传算法和概率鲁棒优化的多目标位置模型。该模型首先使用遗传算法获得初步结果,然后使用概率鲁棒优化找到最优解。初步结果显示,其中的1,3,5个候选站点比其他站点更具成本效益和环境友好性。适应度值收敛在1.55 x 10(-5)的稳定值上,并且Pareto最优边界呈现出可观的聚类特征,这证明了选址优化模型的合理性和可操作性。同时,在给定不确定环境下的鲁棒模型分析达到了进一步优化场地的目的。研究结果可为政府提供建筑拆迁废料回收厂选址的理论依据。 (C)2019 Elsevier Ltd.保留所有权利。

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