针对物流配送中心选址候选集构建中的地理区域离散化问题,提出一种基于k-增长多尺度网格模型的选址区域离散化方法,根据区域选址敏感度不同,进行尺度差异化网格划分.在此基础上,提出了多尺度网格投影及膨胀算法,识别并剔除“限制性区域”及距其指定范围内的多尺度网格.数值实验表明了所提出的模型及算法的有效性.
To the discrete candidate set construction method(division of the continuous geographic district) for distribution center location problem, k-growth multi-scale gridding model is proposed to discrete the continuous geographic district, in which gridding scale varies according to location sensitivity. Furthermore, projection and dilation algorithm for multi-scale grid is given to identify the restriction regions and adjacent grid set within user-defined distance parameter. Finally, numerical experiments on real dataset show the effectiveness of the proposed method.