Control Light Pollution by Genetic Algorithms

Abstract

Based on Light pollution, the team first investigated the important factors that may lead to light pollution, and is divided into three factors, respectively, they are cultural factors, geographical factors and development factors, each and there are several secondary factors, they are GDP, air pollution, river coverage, vegetation coverage, residential coverage, industrial coverage, population quality and other factors. After obtaining these key factors affecting light pollution, our group conducted quantitative modeling based on the two-level AHP hierarchical analysis and derived the weights of these key factors. Noted that because the AHP model largely depends on expert opinion, has a lot of subjectivity, so our group further introduced the grey correlation analysis to more accurately and our assessment results and actual situation is very well, such as protection areas, rural areas for almost no light pollution or light pollution, and urban areas or urban areas are severe or moderate light pollution. Based on the above work, our group adopted the multi-target gene optimization method to obtain the optimal set of strategies, and greatly reduced the light pollution level under the premise that it did not affect the development.