This study aims to optimize the electrical layout of offshore wind farms using advanced algorithms and discusses significance of multimodality in offshore cable design. To achieve this, a multimodal optimization approach is introduced which provides a set of optimized solutions for decision-making. The methodology, termed as Nearest Better Neighbor Clustering-Particle Swarm Optimization (NBNC-PSO), leverages the diversity inherent in multimodal algorithms to yield a range of feasible optimized solutions. The approach begins by calculating costs associated with cables within an offshore wind farm collector system, including cable investment, energy loss, and construction costs by considering the wake impact on the wind turbines. The algorithm then facilitates the exploration of various topological structure, optimal cable type selection, cable connections, substation locations proposing multi-optimized modals. By considering changing wind directions and algorithm parameters, the approach enhances the flexibility and robustness of offshore wind farm designs. The proposed method achieves a 14.42% cost reduction under actual wind conditions, and the largest reduction of 15.89% in cost is observed when the wind direction is shifted by 90°.