遗传算法在蒸汽参数优化中的应用及改进
pplication and Amelioration of GA in Optimization of Steam’s Parameters
选择合适的蒸汽运行参数，对机组经济性有较大的影响。本文以机组蒸汽参数优化为研究内容，针对非线性优化目标的特点，提出了采用遗传算法优化的新思路；并对遗传算法的解码方式、适应度函数、选择和变异方式作了改进，使得参与遗传算法运算的所有个体都是可行解，大大减少了搜索中的无效操作，优化了搜索路径，有效地提高了遗传算法求解的效率和质量。通过算例表明：改进遗传算法的收敛性更好、适应性更强，能更有效地达到或接近全局最优。
hoice of proper reheat parameters has great influence on economic property of unit. According to the nonlinear characteristic of object, optimization of stream’s parameters by means of GA was proposed in this paper, which improved the decoding mode, fitness function, selection and mutation. And this method made all the individual feasible, reduced noneffective operation greatly, and optimized search path, which enhanced calculation efficiency and quality of GA. The results show that the improved hybrid genetic algorithm has better global convergence and adaptability, and could achieve or close holistic optimization much better.
王培红、潘加磊
蒸汽动力工程热力工程、热机工程基础科学
蒸汽参数优化改进遗传算法优化搜索
optimization of steam’s parametersimproved hybrid genetic algorithmoptimization of search path
王培红,潘加磊.遗传算法在蒸汽参数优化中的应用及改进[EB/OL].(2007-04-04)[2025-07-22].http://www.paper.edu.cn/releasepaper/content/200704-92.点此复制
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