Peng Hui Tan

Papers

Total Citations

H-Index

About

Peng Hui Tan’s research focuses on the dynamic scheduling of complex, real-time systems, particularly in the domains of logistics and flexible manufacturing. Her major contributions lie in developing algorithms that coordinate heterogeneous resources—such as mobile robots with varying capabilities or human workers with distinct skills—to efficiently handle tasks that arise unpredictably over time. A key innovation is her work on integrating Internet of Things (IoT) data streams to enable real-time decision-making for pickup and delivery systems, ensuring that time-window constraints are met even as new demands emerge. Her most-cited papers, each garnering 7 citations, address the critical challenge of scheduling under uncertainty: one explores dynamic robot coordination for material transport, while the other tackles precedence relations among tasks in manufacturing. These studies are foundational for advancing autonomous logistics and smart factory operations, demonstrating how adaptive scheduling can boost throughput and reduce delays. Tan’s research is particularly notable for bridging theoretical scheduling models with practical, IoT-enabled implementations, offering scalable solutions for Industry 4.0 environments. Her work continues to inspire further exploration into resilient, real-time resource allocation.