Submarine pipelines have been extensively employed to transport oil or gas from offshore petroleum exploitation activities. To ensure an efficient and expedited pipeline project, a computational tool based on Evolutionary Algorithms is employed to optimize submarine pipeline routes. Different evolutionary optimization methods could be applied, but this study focuses on the Genetic Algorithm (GA). In this tool, each candidate route is evaluated with several criteria incorporated in an objective function, obeying the relevant aspects to be considered in the route design such as: pipeline length, bathymetric data, obstacles, etc. Slope stability verification is also important in landslide risk areas in the pipeline route design context. Thus, this study evaluates the influence of these factors on a representative scenario route configuration. The case study results indicated the slope stability importance in the best route selection. Moreover, the computational tool provides more accurate results, avoids route interpretation mistakes, and ultimately minimizes the huge costs associated with submarine pipeline instalation and operation. Additionally, the slope stability assessment computational costs are low, which indicates the feasibility to incorporate them in the optimization tool.

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