Using simulated annealing for resource allocation
Using simulated annealing for resource allocation
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DOI：
10.1080/13658810210138751
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发表时间：
2002-09-01
影响因子：
5.7
通讯作者：
Heuvelink, GBM
中科院分区：
文献类型：
--
作者：
Aerts, JCJH;Heuvelink, GBM
许多资源分配问题，如土地使用或灌溉规划，需要从广泛的空间数据库输入，并涉及复杂的决策问题空间决策支持系统（SDSS）旨在使这些问题更加透明，并支持资源分配备选方案的设计和评估。这一领域的最新发展集中在利用数学优化技术设计分配计划。通常被称为多准则决策（MCDM）的技术在空间应用中遇到的高维问题时会遇到数值问题。本文介绍了如何使用模拟退火（一种启发式算法）来解决多站点土地使用分配（MLUA）的高维非线性优化问题。问题优化模型既最小化开发成本，又最大化土地利用的空间紧凑度。紧凑度是通过在目标函数中增加一个非线性邻域目标来实现的。西班牙加利西亚的一个案例研究，使用SDSS支持恢复前矿区的新土地使用。
Many resource allocation issues such as land use or irrigation plan ning require input from extensive spatial databases and involve complex decision making problems Spatial decision support systems (SDSS) are designed to make these issues more transparent and to support the design and evaluation of resource allocation alternatives Recent developments in this field focus on the design of allocation plans that utilise mathematical optimisation techniques These techniques often referred to as multi criteria decision making (MCDM) techniques run into numerical problems when faced with the high dimensionality encountered in spatial applications In this paper we demonstrate how simulated annealing a heuristic algorithm can be used to solve high dimensional non linear optimisation problems for multi site land use allocation (MLUA) problems The optimisation model both minimises development costs and maximises spatial compactness of the land use Compactness is achieved by adding a non linear neighbourhood objective to the objective function The method is successfully applied to a case study in Galicia Spain using an SDSS for supporting the restoration of a former mining area with new land use.