<p>Data collection in wireless sensor networks (WSNs) using a mobile sink (MS) is a well-established method for improving network performance and longevity. Among various data collection strategies, rendezvous-point (RP)-based data collection strategies have gained traction due to their ability to reduce communication overhead. However, designing an optimal MS path that minimizes path length and energy consumption simultaneously remains a persistent challenge, primarily due to the NP-hard nature of the problem. Existing approaches often address these objectives in isolation, failing to fully exploit the interplay between path efficiency and energy optimization. This limitation motivates the need for innovative solutions that can balance these dual objectives effectively. In this paper, we present a novel MS path planning framework based on the vortex search algorithm (VSA), designed to overcome these challenges. The proposed scheme introduces a unique solution encoding strategy and a multi-objective fitness function that optimizes both path length and energy utilization. By dynamically determining the optimal number of RPs, the algorithm enhances data collection efficiency while extending network lifetime. This dual-focus optimization not only addresses the limitations of existing methods but also sets a new benchmark in energy-aware MS path planning. Simulation results demonstrate the superiority of the proposed scheme, achieving a 15.25% reduction in energy consumption and a 7.28% increase in network lifetime compared to state-of-the-art methods. These findings underscore the novelty and practical significance of the proposed approach, providing a robust foundation for sustainable and efficient WSN operations.</p>