Stephen Raharja
Papers
1
Total Citations
2
H-Index
1
About
Dr. Stephen Raharja is a rising researcher in multi-agent systems and swarm intelligence, with a focus on autonomous path planning and optimization. His most cited work, "Fair Path Generation for Multiple Agents Using Ant Colony Optimization in Consecutive Pattern Formations" (2024, 2 citations), introduces a novel approach to generating efficient, equitable paths for multiple agents—such as self-driving vehicles—tasked with forming sequential patterns. By leveraging Ant Colony Optimization, Raharja addresses the challenge of minimizing total travel distances while ensuring fairness across agents during formation transitions. This contribution has immediate relevance to logistics, autonomous fleets, and robotic swarms. Though early in his career, his work demonstrates a strong command of bio-inspired algorithms and multi-agent coordination, laying groundwork for scalable, real-time path generation in dynamic environments. As his research gains traction, Raharja is poised to influence both theoretical advances in collective behavior and practical applications in autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1