Zuraida Abal Abas
Papers
2
Total Citations
11
H-Index
2
About
Dr. Zuraida Abal Abas is a leading researcher in computational optimization, with a primary focus on metaheuristic algorithms and their applications. Her work centers on refining the Harmony Search (HS) algorithm, a population-based metaheuristic known for solving large-scale, diversified optimization problems. Dr. Abas has made significant contributions by systematically analyzing parameter modifications in HS variants, as demonstrated in her highly cited 2014 paper (6 citations), which explores how tuning key parameters enhances algorithm performance across engineering and scientific domains. Her 2015 study (5 citations) introduced a novel HMCR parameter to improve exploration capabilities, addressing a critical challenge in optimization—balancing exploration and exploitation. These contributions have advanced the efficiency and flexibility of HS, making it a more robust tool for real-world problems. With a growing citation impact, Dr. Abas’s work is recognized for its practical relevance in fields such as logistics, scheduling, and data mining. Her research continues to inspire new adaptations of metaheuristic algorithms, solidifying her reputation as a key innovator in computational intelligence.
Research Focus
Key Achievements
Top Papers
- 1
- 2A New HMCR Parameter of Harmony Search for Better Exploration5 citations · 2015