Jianghua Ge

Harbin University of Science and Technology

Papers

Total Citations

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About

Dr. Jianghua Ge is a leading researcher in intelligent manufacturing and production scheduling, with a focus on integrating reinforcement learning and multi-agent systems into complex industrial environments. Their most cited work, "Multi-Task Multi-Agent Reinforcement Learning for Real-Time Scheduling of a Dual-Resource Flexible Job Shop with Robots" (2023, 38 citations), addresses the critical challenge of coordinating multiple robots and their supervised machine sets in dynamic job shops. By formulating a mixed integer programming model that simultaneously optimizes job sequencing and robot allocation, Dr. Ge pioneered a real-time scheduling framework that significantly improves efficiency in dual-resource systems. This contribution is particularly impactful for smart factories where robots and human operators collaborate, offering scalable solutions for Industry 4.0 applications. Their research bridges the gap between theoretical multi-agent learning and practical shop-floor control, earning recognition for advancing autonomous decision-making in manufacturing. With a growing citation record, Dr. Ge continues to shape the future of adaptive production systems, making their work essential reading for researchers in operations research, robotics, and AI-driven scheduling.