Application Of Multi-objective Particle Swarm Optimization In Land Consolidation Projects

At present, with the rapid development of economy, society and urbanization, the cultivated land in our country continues to shrink. Land renovation which is an important approach for adherence to the red line of cultivated land and secure a balance between land requisition and compensation, has been always the studying focus of experts and scholars. The prior period site selection of land renovation project planning is a safeguard and foundation for the smooth implementation of the land renovation project planning, but the less research.The site selection of the land renovation project is a multi-objective optimization problem in nature. To solve the multi-objective optimization problem, in particular, using the intelligent algorithm has become a hot topic in the study of multi-objective optimization problems. In this article, the mathematical model of land renovation is established, through the improvement of multi-objective particle swarm optimization algorithm, the site selection model is coupled with the mathematical model, and then the site selection model of land renovation will establish and develop feasibility report.Taking Yima Township, Xiaoyi County, Shanxi Province as an example to verify at last. In order to provide a theoretical reference for the land department to better carry out land renovation work. The main contents are as follows:(1)The design of multi-objective function and constraint system construction on the site selection of land renovationThe multi-objective function and the constraint system of land renovation and location selection were constructed to improve the land quality, optimize the land utilization structure, and promote the intensive utilization of land. The objective function includes the largest new land area, the highest concentrated degree and the highest quality of cultivated land. The constraint system includes the decision variables, the construction scale and the newly-increased cultivated land rate.(2)Design and improvement of Multi-objective Particle Swarm OptimizationThe idea of PSO and its main operating procedures are discussed in the article. And else compare PSO with other intelligent algorithms. The site selection model is coupled with PSO. The pretreatment of date, encoding style, the expressions of updating position, parameter determines are improved then the improved algorithm can adapt to the site selection model. Analysis the Astringency,distribution and error rates through the functions of test algorithms, finally draw a conclusion, the algorithm is feasible.(3) Practical examplesTaking Yima Township, Xiaoyi County, Shanxi Province as an example, a variety of site selection schemes are obtained by assigning different weigh. Through the analysis of different programs, and ultimately determine the best program then conducted a field study to verify its feasibility.