Min Zhang

Artificial Intelligence · with Luo · 2008

A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Min Zhang trusts overall

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

  1. Carlos Artemio Coello Coello
  2. Tapabrata Ray
  3. Kalyanmoy Deb
  4. Jouni Lampinen
  5. Robert A. Ghanea-Hercock
  6. Thomas Philip Runarsson
  7. Efrén Mezura-Montes
  8. Sangameswar Venkatraman
  9. Zixing Cai
  10. Xin Yao

Who trusts Min Zhang overall

  1. Swagatam Das
  2. Efrén Mezura-Montes
  3. Iman Ahmadianfar
  4. Ponnuthurai Nagaratnam Suganthan
  5. Carlos Artemio Coello Coello
  6. Seyedali Mirjalili
  7. Seyed Mohammad Mirjalili
  8. Ali Asghar Heidari
  9. Amir H. Gandomi

Papers from Min Zhang's perspective

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

  1. An Efficient Constraint Handling Method for Genetic Algorithms
  2. No free lunch theorems for optimization
  3. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
  4. Society and civilization: An optimization algorithm based on the simulation of social behavior (IEEE Transactions on Evolutionary Computation)
  5. A generic framework for constrained optimization using genetic algorithms (IEEE Transactions on Evolutionary Computation)
  6. Search biases in constrained evolutionary optimization (IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews))
  7. Stochastic ranking for constrained evolutionary optimization (IEEE Transactions on Evolutionary Computation)
  8. A constraint handling approach for the differential evolution algorithm (Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600))
  9. Problem Deflnitions and Evaluation Criteria for the CEC 2006 Special Session on Constrained Real-Parameter Optimization
  10. Evolutionary Algorithms for Solving Multi-Objective Problems

Their papers