Land use partition method based on tabu search algorithm

Abstract

The invention provides a land use partition method based on tabu search algorithm, aiming to solve the problem that the traditional land use space partition method hardly takes multi-target characteristics of land use into consideration and lacks intelligent and efficient partition decision algorithm. The tabu search algorithm in mathematics field is applied in the land use space partition field; and key issues such as initial plan generation method, neighborhood rule definition, neighborhood generation method, neighborhood search method, memory list update, breadth search, depth search and restarting strategy are modified, a technical method for supporting the land use partition optimization decision is provided, the problem for optimizing spatial unit combination of multi-target in the land use partition is solved better and the problem of hard constraint conditions such as the continuity and integrity of spatial district is considered, so that the partition efficiency is higher and the stability and high efficiency of land use partition process are guaranteed.

Description

technical field [0001] The invention relates to a land use zoning method, in particular to a land use zoning method based on a tabu search algorithm applied in the land use space layout, and belongs to the field of land use planning. Background technique [0002] Land use spatial zoning is a method of dividing the research area into several homogeneous blocks on the basis of comprehensive consideration of various factors (including natural, social, and economic factors) that affect land quality and land use patterns, so as to establish microscopic land use. Utilize the bridge between units and regional land use regulation to achieve sustainable use of land resources. Land use spatial zoning in practical work generally includes land use area zoning, land use use zoning (functional zoning) in overall land use planning, basic farmland protection area division, land development consolidation zoning in special planning, and land evaluation (land Equivalence area division in suit...

AI Technical Summary

Problems solved by technology

However, due to the multi-objective characteristics of land use decision-making, the corresponding spatial optimization decision is required to take into account the multi-objective requirements of land use. These existing methods have certain limitations in solving multi-objective optimization problems, as follows: ①In most cases , usually only a Pareto optimal solution can be obtained by using these methods, and the obtaining of this solution has a great relationship with the parameter setting in the transformation process

② All these algorithms need to select appropriate parameters according to the prior knowledge of the problem, and different parameter settings will lead to different Pareto optimal solutions

③ Some algorithms are very sensitive to the shape of the Pareto optimal front end, and cannot find the Pareto optimal solution in the non-convex area

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