Using linear integer programming for multi-site land-use allocation
Using linear integer programming for multi-site land-use allocation
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DOI：
10.1111/j.1538-4632.2003.tb01106.x
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发表时间：
2003-04-01
影响因子：
3.6
通讯作者：
Stewart, TJ
中科院分区：
文献类型：
--
作者：
Aerts, JCJH;Eisinger, E;Stewart, TJ
空间决策支持 (SDS) 和资源分配领域的研究最近引起了人们对将优化技术与 GIS 集成的越来越多的关注。在本文中，我们讨论使用空间优化技术来解决多地点土地利用分配（MLUA）问题，其中MLUA是指将不同土地利用的多个地点优化分配到一个区域。我们使用四个不同的整数程序 (IP) 来解决 MLUA 问题，其中三个是线性整数程序。 IP 是针对基于栅格的 GIS 环境而制定的，旨在最大限度地降低开发成本并最大限度地提高分配的土地使用的紧凑性。通过包含权重因子，可以实现对成本最小化或紧凑性最大化的偏好。 IP 的评估标准是处理大型数据库的速度和效率。对于 8 x 8 单元的所有区域，所有四个 IP 都在合理的时间内产生了最佳解决方案。最快的模型已成功应用于涉及 30 x 30 单元格区域的案例研究。该案例研究展示了线性 IP 在空间决策支持问题中的实际应用。
Research in the area of spatial decision support (SDS) and resource allocation has recently generated increased attention for integrating optimization techniques with GIS. In this paper we address the use of spatial optimization techniques for solving multi-site land-use allocation (MLUA) problems, where MLUA refers to the optimal allocation of multiple sites of different land uses to an area. We solve an MLUA problem, using four different integer programs (IP), of which three are linear integer programs. The IPs are formulated for a raster-based GIS environment and are designed to minimize development costs and to maximize compactness of the allocated land use. The preference for either minimizing costs or maximizing compactness has been made operational by including a weighting factor. The IPs are evaluated on their speed and their efficacy for handling large databases. All four IPs yielded the optimal solution within a reasonable amount of thne, for all area of 8 x 8 cells. The fastest model was successfully applied to a case study involving an area of 30 x 30 cells. The case study demonstrates the practical use of linear IPs for spatial decision support issues.