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Author: search.filters.author.Rajapaksha, S

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    Shadows on the ivory tower: the unseen scars of academic bullying in South Asia
    (Emerald Publishing, 2025-08-18) Jayasinghe, P.S.K; Kevitiyagala, L; Joshep, K; Rajapaksha, S; Illangamtilake, K; Rathnayake, N
    Purpose Workplace bullying (WB) is increasingly recognised in academic literature. This study aims to investigate the relationship between WB and turnover intentions among academics in Sri Lanka’s higher education sector, focusing on the mediating role of supervisor support (SS). Design/methodology/approach Data were collected via a structured questionnaire from 346 academics using simple random sampling. Structural equation modelling using Smart PLS was used to test the hypothesised relationships. Findings This study reveals a strong positive relationship between WB and employee turnover intention, indicating that academics subjected to bullying are more likely to consider leaving their institutions. Furthermore, SS significantly mediates this relationship, emphasising its role in mitigating the adverse effects of bullying. Research limitations/implications The cross-sectional nature of this study limits the ability to capture long-term dynamics. Future research should incorporate longitudinal or qualitative approaches to explore additional mediating or moderating factors. Originality/value This research fills a critical gap in the literature by focusing on the underexplored Sri Lankan higher education sector, which has received limited scholarly attention. In contrast to prior research that focused on developed nations and other industries, this study provides new insights into the types and impacts of WB in academic institutions. It also underscores the value of SS and offers practical recommendations for creating supportive and retention-friendly work environments.
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    PublicationOpen Access
    Improved Path Planning for Multi-Robot Systems Using a Hybrid Probabilistic Roadmap and Genetic Algorithm Approach
    (Department of Agribusiness, Universitas Muhammadiyah Yogyakarta, 2025-03-24) Jathunga, T; Rajapaksha, S
    This study focuses on the development and application of an improved Probabilistic Roadmap (PRM) algorithm enhanced with Genetic Algorithms (GA) for multi-robot path planning in dynamic environments. Traditional PRM-based methods often struggle with optimizing path length and minimizing turns, particularly in complex, multi-agent scenarios. To address these limitations, we propose a hybrid PRM-GA approach that incorporates genetic operators to evolve optimal paths for multiple robots in real-time.The research contribution is an enhanced PRM-GA framework that improves efficiency in multi-robot navigation by integrating evolutionary techniques for dynamic obstacle handling and optimized path generation.The research methodology involves testing the algorithm in various environments, including varying robot numbers and environmental complexities, to evaluate its scalability and effectiveness. Our results demonstrate that the PRM-GA algorithm successfully reduces both path lengths and turn counts compared to standard PRM-based methods, ensuring collision-free and smooth paths. The algorithm showed robust performance across different scenarios, effectively handling dynamic obstacles and multi-agent coordination. However, in highly dynamic environments with rapidly changing obstacles and constraints, the algorithm may occasionally produce paths with turn counts and distances similar to or slightly higher than those of simpler approaches due to the need for frequent re-optimization. Future research can explore incorporating additional factors such as energy consumption and time optimization, alongside distance and turns, to further enhance the algorithm's efficiency in real-world applications. Overall, the PRM-GA approach advances the state of the art by offering a more adaptable and scalable solution for multi-robot path planning, with applications in logistics, industrial automation, and autonomous robotics.