Lin Shi

Artificial Intelligence · with Tan · 2021

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Lin Shi trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Yaochu Jin
  2. Kalyanmoy Deb
  3. Thomas Bäck
  4. Ozgur Yeniay
  5. Tetsuyuki Takahama
  6. Ryoji Tanabe
  7. Zhenyu Yang
  8. J. Branke
  9. Handing Wang

Papers from Lin Shi's perspective

Ordered by how strongly the researchers Lin Shi trusts endorse each paper. Same corpus, a different order for every researcher.

  1. An Efficient Constraint Handling Method for Genetic Algorithms
  2. Surrogate-assisted evolutionary computation: Recent advances and future challenges
  3. Large scale evolutionary optimization using cooperative coevolution (Information Sciences)
  4. A comprehensive survey of fitness approximation in evolutionary computation (Soft Computing - A Fusion of Foundations, Methodologies and Applications)
  5. Evolutionary Computation: Towards a New Philosophy of Machine Intelligence
  6. A fast and elitist multiobjective genetic algorithm: NSGA-II
  7. Constrained Optimization by the ε Constrained Differential Evolution with Gradient-Based Mutation and Feasible Elites (International Conference on Evolutionary Computation)
  8. A Multi-population Approach to Dynamic Optimization Problems
  9. Multi-objective optimization using evolutionary algorithms
  10. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition (IEEE Transactions on Evolutionary Computation)

Their papers