基于改进型遗传算法的能源模糊优化的研究  

Fuzzy optimization of energy by improved genetic algorithm

作　　者：王化兰[1] 任艳[1] 

机构地区：[1]中国石油大学(华东)计算机通信工程学院,山东东营257061

出　　处：《计算机工程与设计》2007年第15期3652-3655,共4页Computer Engineering and Design

摘　　要：将模糊优化的概念引入能源模型中,将多目标能源模型中的能源、经济和环境3个目标函数的约束条件模糊化,并定义了由惩罚函数和目标函数组成的新目标函数。针对该模糊多目标优化模型,采用改进型遗传算法进行求解,在适应度函数以及其它遗传操作的设计上做了改进。实验表明,这种遗传算法是一种性能优良的解决能源优化问题的启发式搜索算法,可以快速有效的求得能源优化问题的最优解,进而得到能源的最佳配置。Fuzzy optimization is introduced into energy models. Constraints of the energy, economic and environmental in multiobjective model of energy are fuzzed. And they defined the new objective function by the composition of penalty Function and the objective function. In view of the fuzzy multi-objective optimization model, they improved genetic algorithm. It made improvements in the design of the fitness function and genetic manipulation. Experiments show that the genetic algorithm is an excellent heuristic algorithm to solve energy optimization. It can achieve the optimal solution of the energy optimization problem quickly and effectively. And then it can find the best allocation of energy.

关 键 词：遗传算法 模糊优化 多目标优化模型 能源模型 能源配置 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] O224[自动化与计算机技术—控制科学与工程]