摘要
针对传统的采用二进制编码的遗传算法在求解大规模机组组合问题时收敛速度慢、易早熟等问题,作者结合机组组合问题的特点,提出了一种混合智能遗传算法。该算法以机组状态作为个体编码,结合启发式方法的自适应智能变异算子求解目标函数,显著缩小了求解问题的规模,保证了群体多样性,提高了算法的搜索效率,改善了算法的收敛性。仿真计算结果表明了该算法的有效性和实用性。
When traditional binary-coded genetic algorithm (GA) was used in the commitment of large scale generating units, the defects of this algorithm such as low convergence speed and precocity might appear. According to the features of unit commitment (UC) the authors proposed a hybrid intelligent GA. Taking the unit states as genotypes and combining with heuristic adaptive intelligent variation operator, the proposed algorithm solved the objective function, therefore, the scale of the solved problem was notably reduced, the colony diversity was ensured, the search efficiency and convergence of the proposed algorithm were improved. The results of simulation show that the proposed algorithm is effective and practicable.
出处
《电网技术》
EI
CSCD
北大核心
2004年第19期47-50,共4页
Power System Technology
