Abstract
Designing low-cost network layouts is an essential step in planning linked infrastructure. For the case of capacitated trees, such as oil or gas pipeline networks, the cost is usually a function of both pipeline diameter (i.e. ability to carry flow or transferred capacity) and pipeline length. Even for the case of incompressible, steady flow, minimizing cost becomes particularly difficult as network topology itself dictates local flow material balances, rendering the optimization space non-linear. The combinatorial nature of potential trees requires the use of graph optimization heuristics to achieve good solutions in reasonable time. In this work we perform a comparison of known literature network optimization heuristics and metaheuristics for finding minimum-cost capacitated trees without Steiner nodes, and propose novel algorithms, including a metaheuristic based on transferring edges of high valency nodes. Our metaheuristic achieves performance above similar algorithms studied, especially for larger graphs, usually producing a significantly higher proportion of optimal solutions, while remaining in line with time-complexity of algorithms found in the literature. Data points for graph node positions and capacities are first randomly generated, and secondly obtained from the German emissions trading CO2 source registry. As political will for applications and storage for hard-to-abate industry CO2 emissions is growing, efficient network design methods become relevant for new large-scale CO2 pipeline networks.
Highlights
Network design problems arise in a multitude of scenarios
We provide three examples of local heuristics that serve as basis for exploring metaheuristics later, serving as baselines for comparison with our contributions
For the smaller network comparisons, optimal networks were discovered through a brute force method, obtained by comparing all the possible trees, obtained from Prüfer sequences (Prüfer 1918)
Summary
Network design problems arise in a multitude of scenarios. For fluid transport problems, such as oil or gas pipeline networks, the aim is to link all fixed points of the network via pipelines while matching fluid supply to demand and minimizing a defined cost-function. Networks that distribute a new commodity to a series of known recipients such as Hydrogen (André et al 2013) or biogas networks (Heijnen et al 2020), will use an identical design process. All cases involve linking a series of fixed sources/sinks points via pipelines with associated capacity and cost. These cases are functionally identical, for clarity we consider here the multi-source, singlesink case that is local CO2 collection networks. The methods studied here are applicable to multi-source, multi-sink scenarios, as long as sink and source capacities are defined, and total source and sink capacity match
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