Weimin Tan

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About

Weimin Tan is a researcher whose work bridges advanced optimization, production planning, and industrial robotics, with a focus on enhancing manufacturing efficiency. His key research areas include bi-level programming, order acceptance, and production scheduling, particularly within the context of industrial robot manufacturing. Tan’s most notable contribution is his 2024 paper, "Bi-level programming for joint order acceptance and production planning in industrial robot manufacturing enterprise," which has garnered 11 citations—a strong early impact for a recent publication. This work introduces a novel bi-level optimization framework that simultaneously addresses order acceptance and production planning, enabling manufacturers to make more informed decisions under capacity constraints. The model’s practical relevance is underscored by its application to real-world industrial robot enterprises, where it helps balance profitability and operational feasibility. Tan’s research is distinguished by its integration of theoretical optimization with tangible manufacturing challenges, offering actionable insights for both academics and industry practitioners. His contributions are particularly valuable as the manufacturing sector increasingly adopts automation and data-driven decision-making, positioning him as a rising voice in operations research and industrial engineering.