Miqing Li

Papers

Total Citations

217

H-Index

About

Dr. Miqing Li is a leading researcher in evolutionary computation and multi-objective optimization, with a particular focus on complex manufacturing and disassembly systems. His work bridges the gap between theoretical algorithm design and practical industrial challenges, especially in sustainable production and remanufacturing. Dr. Li has made significant contributions to the development of evolutionary many-objective optimization algorithms for mixed-model disassembly line balancing with multi-robotic workstations—a critical problem in end-of-life product processing. His 2018 paper on this topic has garnered 99 citations, while his 2019 work incorporating simulated annealing for interval processing time uncertainty has reached 118 citations. These highly cited papers address the real-world complexity of disassembly lines where robots with varying capacities perform tasks simultaneously, accounting for uncertainty in processing times and energy consumption. Dr. Li’s research is notable for its practical impact on improving efficiency and sustainability in manufacturing, offering robust solutions that optimize multiple conflicting objectives. His work continues to influence both the evolutionary computation community and industrial engineering practitioners seeking to automate and optimize disassembly processes.