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A method for designing minimum‐cost multisource multisink network layouts
Systems Engineering ( IF 2 ) Pub Date : 2019-05-30 , DOI: 10.1002/sys.21492
Petra W. Heijnen 1 , Emile J.L. Chappin 1 , Paulien M. Herder 1
Affiliation  

Systems engineers are equipped to design complex networked systems such as infrastructures. A key goal is cost minimization over a vast solution space. However, finding a minimum‐cost system while comprehensively satisfying different stakeholders is challenging and lacks proper methodological support. Stakeholders often employ their own expert estimations for lack of suitable decision‐support methods. In these settings, systems engineers typically require mid‐fidelity, easy‐to‐use methods. We present a rigorous method that quickly finds minimum‐cost solutions for networks with multiple sources and sinks, focusing on pipeline topology, length, and capacity. It can serve as a discussion tool in multiactor design processes, to demarcate the design space, indicate sources of uncertainty, and provoke further analyses, different designs, or contractual negotiations. It is applicable to a wide variety of cases, including many prominent infrastructures needed to mitigate CO₂. We prove that the optimal layout is a minimum‐cost Gilbert tree, and develop a heuristic based on the Gilbert‐Melzak method. We demonstrate the method's efficacy for a case set regarding solution quality, computational time, and scalability. We also show its efficiency and usefulness for systems engineers in real‐world settings. Systems engineers can use the generated cost‐optimal system designs to benchmark any design changes in real‐world negotiation processes.

中文翻译:

一种设计成本最低的多源多接收器网络布局的方法

系统工程师具备设计复杂的联网系统(例如基础架构)的能力。一个关键的目标是在广阔的解决方案空间内将成本降至最低。但是,要找到一个最低成本的系统,同时要全面满足不同利益相关者的需求,这是一个挑战,并且缺乏适当的方法论支持。由于缺乏合适的决策支持方法,利益相关者经常采用自己的专家估计。在这些设置中,系统工程师通常需要中等保真度,易于使用的方法。我们提出了一种严格的方法,可以快速找到具有多个源和接收器的网络的最低​​成本解决方案,重点是管道拓扑,长度和容量。它可以用作多角色设计过程中的讨论工具,以划定设计空间,指出不确定性的来源,并引发进一步的分析,不同的设计,或合同谈判。它适用于各种情况,包括减轻CO 2所需的许多重要基础设施。我们证明最优布局是最小成本的吉尔伯特树,并基于吉尔伯特·梅尔扎克方法开发了启发式算法。我们证明该方法对于解决方案质量,计算时间和可伸缩性的案例集的有效性。我们还向现实世界中的系统工程师展示了它的效率和实用性。系统工程师可以使用生成的成本最优的系统设计来对实际谈判过程中的任何设计更改进行基准测试。我们证明该方法对于解决方案质量,计算时间和可伸缩性的案例集的有效性。我们还向现实世界中的系统工程师展示了它的效率和实用性。系统工程师可以使用生成的成本最优的系统设计来对实际谈判过程中的任何设计更改进行基准测试。我们证明该方法对于解决方案质量,计算时间和可伸缩性的案例集的有效性。我们还向现实世界中的系统工程师展示了它的效率和实用性。系统工程师可以使用生成的成本最优的系统设计来对实际谈判过程中的任何设计更改进行基准测试。
更新日期:2019-05-30
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