An improved artificial immune system for seeking the Pareto front of land-use allocation problem in large areas
An improved artificial immune system for seeking the Pareto front of land-use allocation problem in large areas
复制标题
一种改进的人工免疫系统，用于寻求大区域土地利用分配问题的帕累托前沿
DOI：
10.1080/13658816.2012.730147
复制
发表时间：
2013-05-01
影响因子：
5.7
通讯作者：
He, Shenjing
中科院分区：
文献类型：
--
作者：
Huang, Kangning;Liu, Xiaoping;He, Shenjing
帕累托前沿可以通过揭示多个相互冲突的目标之间可能的权衡，为土地利用规划决策提供有价值的信息。然而，寻找土地利用分配的帕累托前沿比寻找唯一的最优解决方案困难得多，特别是在处理大面积区域时。本文提出了一种改进的多目标土地利用分配人工免疫系统（AIS-MOLA）来解决这一具有挑战性的任务。所提出的 AIS 配备了三个修改后的算子，即（1）基于折衷编程的启发式超突变，（2）基于非支配邻居的比例克隆和（3）保留连接补丁的新颖交叉算子。为了验证所提出的算法，将其应用于假设的土地利用分配问题。与Pareto模拟退火（PSA）方法相比，AIS-MOLA可以生成更接近Pareto前沿的解，计算时间仅为PSA的5.1%。此外，AIS-MOLA还应用于中国广东番禺大面积小区的案例研究。实验结果表明，该算法即使处理大面积的土地利用分配问题，也能够生成近似真实Pareto前沿的最优替代解。此外，这些解的分布可以定量地展示研究区域空间适宜性和紧凑性之间的复杂权衡。软件和补充材料可在http://www.geosimulation.cn/AIS-MOLA/获取。
The Pareto front can provide valuable information on land-use planning decision by revealing the possible trade-offs among multiple, conflicting objectives. However, seeking the Pareto front of land-use allocation is much more difficult than finding a unique optimal solution, especially when dealing with large-area regions. This article proposes an improved artificial immune system for multi-objective land-use allocation (AIS-MOLA) to tackle this challenging task. The proposed AIS is equipped with three modified operators, namely (1) a heuristic hypermutation based on compromise programming, (2) a non-dominated neighbour-based proportional cloning and (3) a novel crossover operator that preserves connected patches. To validate the proposed algorithm, it was applied in a hypothetical land-use allocation problem. Compared with the Pareto Simulated Annealing (PSA) method, AIS-MOLA can generate solutions more approximate to the Pareto front, with computation time amounting to only 5.1% of PSA. In addition, AIS-MOLA was also applied in the case study of Panyu, Guangdong, PR China, a large area with cells. Experimental results indicate that this algorithm, even dealing with large-area land-use allocation problems, is capable of generating optimal alternative solutions approximate to the true Pareto front. Moreover, the distribution of these solutions can quantitatively demonstrate the complex trade-offs between the spatial suitability and the compactness in the study area. Software and supplementary materials are available at http://www.geosimulation.cn/AIS-MOLA/.