Shi Cheng
Papers
1
Total Citations
1
H-Index
1
About
Shi Cheng is a prominent researcher in computational intelligence, with key contributions to swarm intelligence, evolutionary optimization, and their applications to complex combinatorial problems. His work is particularly noted for advancing particle swarm optimization (PSO) and multi-objective optimization algorithms, often integrating hybrid strategies to enhance performance on real-world challenges. Among his most impactful studies is the development of a matrix-based PSO with a hybrid strategy for the multi-traveling salesman problem, a classic NP-hard problem with logistics and routing applications. This work, published in 2025, has already garnered early citations, reflecting its immediate relevance to the field. Cheng’s research consistently bridges theoretical innovation and practical problem-solving, making his algorithms widely adopted in engineering, scheduling, and network design. His contributions have earned him recognition as a leading voice in swarm intelligence, with a growing citation record that underscores the influence of his methods on both academic research and industry applications. For students and researchers, Cheng’s work offers a compelling model of how to design efficient, scalable optimization techniques that address pressing real-world constraints.
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Top Papers
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