Automatic Districting of Land Consolidation Based on Multi-objective Tabu Search Algorithm
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Abstract
Land consolidation districting is vital and pivotal for the land exploitation and consolidation planning. At present, the main measures, including overlaying method, dominant sign method and constellation clustering method, have several essential defects, such as lacking maneuverability, low automatization and high influenced by artificial experience. In fact, because of holding a set of canonical principles and restrictions, land consolidation districting is essentially a kind of multi-objective spatial districting problem, which can be automatically resolved by the multi-objective optimization model. So, we put up a MOTS (multi-objective tabu search) algorithm to solve the problem, and describe the program flow and core issues in detail. Finally, we take a case study of farmland consolidation districting in Jiaxia District of Hubei Province to exam the correctness of the model.
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