Dual Coding Hybrid Genetic Algorithm for Optimal Schedule of Pumping Stations in Multi-Sources Water Injection System
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摘要: 以耗电量最小为目标函数,排量、压力等限制为约束条件,建立了多源注水系统泵站优化调度数学模型。遗传算法采用了二进制编码和实数编码相结合的双重编码,并调整了适应函数,采用随机多父辈适应函数值加权交叉和多种变异操作,结合模拟退火算法,给出了初温的确定方法,形成了混合遗传算法。该算法能够有效地提高收敛速度,避免早熟收敛。同时在操作过程中,给出了泵排量的处理方法,使各水量约束条件得到满足,减少了不可行解的产生。算例说明了该优化方法的有效性。Abstract: A mathematical model for the optimal schedule of water injection pumping stations is established, in which the minimum electric power consumption is taken as the objective function, and the restrictions to the displacement and pressure are taken as constraint conditions. In the genetic algorithm dual coding is adopted, the fitness function is adjusted, and random parent-number fitness-weighted cross and many mutation methods are adopted. The simulated annealing algorithm is combined to give the method of determining initial temperature, thus the hybrid genetic algorithm is formed. It can improve the speed of convergence and avoid premature convergence. A processing method of displacement is proposed, so the displacement restrictions are satisfied and the number of infeasible solutions is reduced. Example shows that the algorithm is efficient.
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