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成品油管道开泵方案优化研究可以较大幅度降低管道运行能耗。采用动态规划算法(Dynamic Programming,DP)求解,管道较长时计算效率较低;采用基本遗传算法(Simple Genetic Algorithm,SGA)求解,存在求解结果最优性不高等问题。在对成品油管道运行过程中开泵方案优化问题深入分析以及对并行计算技术深入理解的基础上,应用模拟退火遗传算法粗粒度模型(Coarse-Grained Simulated Annealing-Genetic Algorithm,CGSAGA)进行较大规模成品油管道开泵方案优化研究。以某条实际运行的成品油管道为例进行计算,结果表明:CGSAGA从求解效率与结果最优性均优于传统串行算法,为成品油管道开泵方案优化快速、准确制定提供了有效的途径。
Optimization of open-pump program of refined oil pipeline can greatly reduce the energy consumption of pipeline operation. The dynamic programming (DP) method is used to solve the problem. When the pipeline length is longer, the computational efficiency is lower. Using Simple Genetic Algorithm (SGA) solves the problem that the optimal solution is not high. On the basis of in-depth analysis of the optimization of the pump-open plan during the operation of the refined oil pipeline and the deep understanding of the parallel computing technology, a large scale (Coarse-Grained Simulated Annealing-Genetic Algorithm, CGSAGA) Optimization of Pumping Plan for Product Oil Pipeline. Taking an actual product pipeline as an example, the results show that CGSAGA is superior to the traditional serial algorithm from the efficiency of solution and the optimality of the result, which provides an effective and effective way to optimize the open pump scheme of the refined oil pipeline way.