基于GATS算法的城市土地使用规划问题研究

Land Use Development Plan Based Genetic Algorithm and Tabu Search Algorithm

土地使用规划就是确定和选择可能的发展区域以满足使用土地的要求 (包括新区域的形成及提供公共服务设施 ) ,最优土地发展规划就是从许多可能的发展区域和人口分配方案中选择最好的方案 ,这一问题能归结为一个单目标 0 -1规划问题。本文根据遗传算法和禁忌搜索算法自身的优势与不足 ,提出一种将二者混合使用求解土地使用规划的算法 ,以使总的费用最少 ,同时针对此模型中约束函数的特点 ,提出一种处理约束的新方法 ,并用实际问题进行了数值实验。

The land use planning consists of identifying and selecting potential development areas to meet the expected land requirements. The optimal land use development relates to the allocation of population with optimal objective function value. The optimal land use development plan is chosen from a large number of potential development areas and potential population allocation. Land use development plan problem can be formulated as a 0-1 programming problem mathematically. In this paper, the genetic algorithm and tabu search algorithm are used to solve the 0-1 programming problem in which some new land use plans are identified in Hong Kong so as to minimise the total development and transportation cost. It is the first work to apply genetic algorithm and tabu search for land use problem in practice. The developed model will advance this subject and help the authorities decide which new residential areas should be considered for detailed investigation. The Hong Kong 2006 planning data are used for case study.