传统遗传算法和改进的NSGA-Ⅱ算法在多目标优化问题的应用

The Traditional Genetic Algorithm and Improved NSGA-Ⅱ Algorithm in the Application of Multi-objective Optimization Problem

在电力产业蓬勃发展的今天,随着一系列电力改革措施的实行,火电企业需要多角度深层次的考虑降低电厂运行成本。在火力发电过程中产生很多污染,如二氧化硫,氮氧化物,二氧化碳等。采用多目标优化的方法对火电厂负荷分配问题进行研究具有重要意义。以考虑经济和环境的双目标优化为例子,运用传统的简单遗传算法和改进的遗传算法-NSGA-Ⅱ,以三机组为例,进行优化计算,并且进行研究。

With the electric power industry vigorous development nowadays, along with a series of electric power reform measures implemented, thermal power enterprise need multi- angle deep consider reducing power plant operation cost. In the process of thermal power produced a lot of pollution, such as sulfur dioxide and nitrogen oxides, carbon dioxide and so on. Using the method of multi-objective optimization problems of power load distribution has a great significance for the study. This paper consider economic and environmental double objective optimization for example, the use of traditional simple genetic algorithm and improved genetic algorithm - NSGA - Ⅱ , with three unitfor example, were optimized, and do a comparative study.