Rudi NurdiansyahI-HSUAN HONGJack C. P. Su2025-05-062025-05-062025https://www.scopus.com/record/display.uri?eid=2-s2.0-105000970782&origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/728937To enhance the design and layout of marine farms, while addressing the ambiguity of environmental parameters, this study proposes a non-parametric, scenario-based robust bi-level optimization model for the marine current turbine installation problem (BO-MCTIP). In this model, the upper level determines the number and locations of marine current turbines (MCTs), while the lower level determines how to connect the installed MCTs. First, all scenarios in the model are solved using a novel greedy heuristic algorithm (GHA), which minimizes the cost per watt by considering wake effects and submarine power cable connection costs. GHA outperforms the complete search and random search algorithms. Then, using the solutions obtained by GHA in the BO-MCTIP, the min–max relative regret decision rule is used to identify a robust solution. The result from a test case in Cook Inlet, Alaska, demonstrates that the robust solution performs effectively across all scenarios considered in the proposed model.installation problemmarine current turbineoptimizationParameter ambiguitywake effect[SDGs]SDG7[SDGs]SDG14journal article10.1080/0305215X.2024.2446591