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Optimization Of Natural Gas Pipeline Transportation Using Ant Colony Optimization

机译:基于蚁群算法的天然气管道运输优化

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In this paper, an ant colony optimization (ACO) algorithm is proposed for operations of steady flow gas pipeline. The system is composed of compressing stations linked by pipelegs. The decisions variables are chosen to be the operating turbocompressor number and the discharge pressure for each compressing station. The objective function is the power consumed in the system by these stations. Until now, essentially gradient-based procedures and dynamic programming have been applied for solving this no convex problem. The main original contribution proposed, in this paper, is that we use an ACO algorithm for this problem. This method was applied to real life situation. The results are compared with those obtained by employing dynamic programming method. We obtain that the ACO is an interesting way for the gas pipeline operation optimization.
机译:本文提出了一种用于稳定流燃气管道运行的蚁群优化算法。该系统由通过支腿链接的压缩站组成。选择决策变量作为每个压缩机站的工作涡轮压缩机数量和排气压力。目标函数是这些站在系统中消耗的功率。迄今为止,基本上已经采用基于梯度的过程和动态编程来解决这个无凸问题。本文提出的主要原始贡献是,我们针对此问题使用了ACO算法。该方法应用于现实生活中。将结果与采用动态编程方法获得的结果进行比较。我们认为,ACO是优化天然气管道运行的有趣方式。

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