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"Three-line" collaborative-optimization-oriented multi-agent genetic algorithm

A multi-agent and genetic algorithm technology, applied in the fields of genetic rules, computing, data processing applications, etc.

Active Publication Date: 2018-05-01
WUHAN UNIV
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Problems solved by technology

The above model has played its due role in the optimal allocation of land use, but it has certain limitations in the face of "three-line" conflicts and coordinated optimization of land use spatially complex systems.

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  • "Three-line" collaborative-optimization-oriented multi-agent genetic algorithm
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  • "Three-line" collaborative-optimization-oriented multi-agent genetic algorithm

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[0068] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0069] please see figure 1 , the technical solution adopted in the present invention is: a multi-agent genetic algorithm facing "three lines" collaborative optimization, comprising the following steps:

[0070] Step 1: Taking Wuhan City as the research area and 2020 as the planning time point, collect and process the data sets of the research area, including data set A, data set B, and data set C; data set A includes ecological protection red line, cultivated land and Basic farmland protection red line, urban expansion boundary line and other "three-line" sp...

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Abstract

The invention relates to a "three-line" collaborative-optimization-oriented multi-agent genetic algorithm. The algorithm includes: collecting and processing study-area data sets of A, B and C; adopting the data set of A to carry out superposition diagnosis analysis on study-area "three-line" space to acquire a "three-line" conflict space distribution graph; carrying out raster conversion on the "three-line" conflict space distribution graph acquired in the step 2; setting an optimization objective and corresponding weights of the multi-agent genetic algorithm, and constructing a fitness function; combining the data sets of A, B and C to set constraint conditions of the multi-agent genetic algorithm; setting conversion rules and algorithm parameters, which include a chromosome population size, a crossover rate, a mutation rate and a maximum iteration number of the multi-agent genetic algorithm; constructing a multi-agent genetic-algorithm model; and optimizing result output. The algorithm solves the problems that current "three-line" space conflicts in "multiple-rules-in-one" are difficult to coordinate, space configuration efficiency is low, intelligent behaviors of multiple agentsare difficult to simulate, and thus poor configuration result rationality and the like are caused.

Description

technical field [0001] The invention belongs to the field of geographic information science and technology, and relates to an improved multi-agent genetic algorithm for collaborative optimization of "three lines" such as land use ecological protection red line, cultivated land and basic farmland protection red line, and urban expansion boundary. Background technique [0002] Spatial optimization is one of the most complex unstructured problems that human beings often face. It is based on the understanding of objective laws, through the correction and adjustment of the unreasonable spatial pattern in the current situation, to promote the continuous improvement of the spatial pattern and the relationship between spatial elements. The process of continuous coordination to achieve greater comprehensive benefits. Many complex spatial problems in the field of geography research can ultimately be attributed to space optimization problems, such as facility location (parks, hospitals...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/12G06Q10/02
CPCG06N3/126G06Q10/02
Inventor 刘耀林王好峰袁满唐巍
Owner WUHAN UNIV
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