基于模拟退火遗传算法的自压树状管网优化

将遗传算法全局优化和模拟退火的良好局部搜索能力有机结合，构造出一种退火遗传算法用于自压树状管网的优化设计方法。假定管网中每一管段最多只能由两种管径的管道组成，建立了以管网造价为目标函数，以管长、标准管径为决策变量的自压树状管网优化数学模型。采用基于不可行度的退火算法处理约束条件，应用遗传算法进行优化计算。仿真实例结果表明，该模型与算法在求解自压树状管网优化问题上，具有良好的优化性能和求解效率。

Optimization of gravity pipe network based on annealing genetic algorithm

The genetic algorithm for global optimization is combined with annealing simulation approach to establish an annealing genetic algorithm for optimization design of gravity pipe network. By assuming every section of pipeline is composed of two kinds of pipe with different diameters and regarding the cost as the objective function, the pipe length and standard diameter as decision variables, a mathematical model for optimization of the gravity tree pipe network is established. In the model, the annealing algorithm processing constraint based on infeasible degree is adopted and the genetic algorithm is applied to carry out the optimization. The application shows that the proposed model and algorithms are effective and possess high efficiency in calculation.