Krishnendu Sanyal

Computational Theory and Mathematics · 2017

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom Krishnendu Sanyal trusts overall

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

  1. Kalyanmoy Deb
  2. Qingfu Zhang
  3. Eckart Zitzler
  4. Hui Li
  5. Himanshu Jain
  6. Ke Li
  7. Lothar Thiele
  8. Joshua D. Knowles
  9. Hisao Ishibuchi

Who trusts Krishnendu Sanyal overall

  1. Ryoji Tanabe
  2. Zhi-Zhong Liu
  3. Yong Wang
  4. Zhongwei Ma

Papers from Krishnendu Sanyal's perspective

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

  1. A fast and elitist multiobjective genetic algorithm: NSGA-II
  2. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition (IEEE Transactions on Evolutionary Computation)
  3. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results (Evolutionary Computation)
  4. A review of multiobjective test problems and a scalable test problem toolkit (IEEE Transactions on Evolutionary Computation)
  5. SPEA2: Improving the Strength Pareto Evolutionary Algorithm For Multiobjective Optimization
  6. Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II (IEEE Transactions on Evolutionary Computation)
  7. An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints (IEEE Transactions on Evolutionary Computation)
  8. Scalable multi-objective optimization test problems (Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600))
  9. An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point Based Nondominated Sorting Approach, Part II: Handling Constraints and Extending to an Adaptive Approach (IEEE Transactions on Evolutionary Computation)
  10. Decomposition of a Multiobjective Optimization Problem Into a Number of Simple Multiobjective Subproblems (IEEE Transactions on Evolutionary Computation)

Their papers