基于遗传算法的动力配煤模型

遗传算法作为一种函数优化方法，不依赖于求解问题的本身，利用简单的编码技术和繁殖机制，快速有效地搜索复杂、高度非线性和多维空间，寻求最优解．动力配煤是一个多元优化问题，混煤与各组成单煤间的非线性关系增加了约束条件向确定性方程转化的难度．将遗传算法用于动力配煤方案优化，利用其全局性、并行性、快速性的特点，有效地解决了配煤中的非线性多约束问题，取得了理想的效果．

Optimization model for power coal blending based on genetic algorithm

As an optimization function, genetic algorithm is independent of problem itself. It makes use of the simple coding technology and propagation mechanism, search optimal result rapidly in complex nonlinear multidimensional space. Power coal blending is a process of multi object optimization. The relationship between blending coal and single coal is nonlinear. It adds to the difficulty of the transform from restriction to definite equation. In this paper, the author apply genetic algorithm to power coal blending problem. With universality and parallelism, GA can settle the nonlinear restriction of coal blending problem effectively. We acquire preferable result through examination.