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The Use of the Multi-objective Ant Colony Optimization Algorithm in Land Consolidation Project Site Selection

机译:多目标蚁群优化算法在土地整理项目选址中的应用

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The present study abstracts the land consolidation project site selection (LCPSS) problem to a multi-objective spatial optimization problem. In view of the shortcomings of traditional site selection methods in coordinating multiple objectives, the present study, considering the scale-related constraint conditions and general site selection rules of land consolidation, proposes a multi-objective LCPSS model (MOLCPSSM) based on an ant colony optimization algorithm with social, economic and ecological benefits as the optimization objectives. In addition, the present study focuses on the investigation of the mapping and coding relationships between the artificial ants and vector patches and also improves the ants' spatial unit selection scheme and pheromone update mechanism. Furthermore, the present study verifies the MOLCPSSM through a case study of Jiayu County, Hubei Province, China. The results demonstrate the operability of the MOLCPSSM in solving practical land consolidation problems.
机译:本研究将土地整理项目选址(LCPSS)问题抽象为多目标空间优化问题。鉴于传统选址方法在协调多目标方面的缺陷,本研究在考虑规模相关约束条件和土地整理的一般选址规则的基础上,提出了一种基于蚁群的多目标LCPSS模型(MOLCPSSM)。以社会,经济和生态效益为优化目标的优化算法。此外,本研究着重研究了人工蚂蚁与矢量补丁之间的映射和编码关系,并改进了蚂蚁的空间单位选择方案和信息素更新机制。此外,本研究以中国湖北省嘉yu县为例,对MOLCPSSM进行了验证。结果证明了MOLCPSSM在解决实际土地整理问题方面的可操作性。

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