Peisheng Liu
Papers
4
Total Citations
25
H-Index
3
About
Peisheng Liu is a leading researcher in sustainable manufacturing and operations research, specializing in the optimization of disassembly line systems for end-of-life products. Their work focuses on critical challenges in robotic and human-robot collaborative disassembly, addressing complex balancing problems under resource and environmental constraints. Liu’s major contributions include pioneering multi-objective optimization algorithms—such as the Multi-Objective Ant Lion Optimizer and discrete strength Pareto evolutionary algorithm—to enhance efficiency, reduce energy consumption, and maximize profit in disassembly processes. Their research on stochastic robotic disassembly line balancing, multi-product partial U-shaped lines, and hybrid human-robot systems has provided foundational models for industry adoption. With over 25 citations across key publications from 2021–2022, Liu’s work is gaining traction among scholars and practitioners aiming to integrate automation and sustainability. Notable achievements include developing an improved Tabu Search algorithm for multi-robot systems and a multi-neighborhood parallel greedy search for collaborative disassembly, advancing the field toward smarter, greener manufacturing. Liu’s research is essential reading for those interested in circular economy, industrial engineering, and intelligent production systems.
Research Focus
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Top Papers
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