摘要
针对实数遗传算法应用于火电厂机组负荷优化组合问题中存在早熟收敛的难题,提出了部分解约束结合惩罚函数的改进实数遗传算法,在解除约束条件的方法、变异操作策略、种群初始化等多方面针对火电厂机组负荷优化组合问题的自身特点对实数遗传算法提出了新的改进思路,解决了实数遗传算法应用于多峰值优化问题中早熟而收敛于局部极值点的难题,对某5台机组的火电厂机组负荷优化组合的优化仿真表明,采用该方法改进后的遗传算法优化成功率能达到100%。
To address the optimization premature convergence problem of unit commitment problem （UCP） in power plant with float genetic algorithms （FGA）, a refined FGA with the constrained conditions of partially solved combined with punishing function （FGA-PPF） were introduced FGA-PPF refined in the dealing with its constrained conditions, the strategy of mutation, initialization of population of FGA with respect to the features of UCR FGA-PPF resolved the problem of pre-mature in FGA , in the application to a five units power plant UCP, The results shows that the optimization success rate can reach 100% with the FGA-PPE.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2009年第2期107-112,共6页
Proceedings of the CSEE
关键词
实数遗传算法
机组优化组合
部分解约束
早熟
收敛
float problem
constrained convergence genetic algorithms
conditions partially umts commitment solved
premature
