Bo D. Wang

Computational Theory and Mathematics · 2016

A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 61 citations into it; #3,348 of 12,182 by trust here, #3,448 by citations
• Artificial Intelligence — 54 citations into it; #11,715 of 35,345 by trust here, #16,471 by citations
• Management Science and Operations Research — 14 citations into it; #3,074 of 11,946 by trust here, #3,457 by citations
• Statistics and Probability — 7 citations into it

Whom Bo D. Wang trusts overall

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

1. Kalyanmoy Deb
2. Eckart Zitzler
3. Qingfu Zhang
4. Hui Li
5. Miqing Li
6. Shengxiang Yang
7. Johannes Bader
8. Juan José Durillo
9. Christian Igel
10. Lothar Thiele

Who trusts Bo D. Wang overall

1. Ye Tian
2. Yanan Sun
3. Shouyong Jiang
4. Hisao Ishibuchi
5. Ran Cheng
6. Xing-yi Zhang
7. Gary G. Yen
8. Ryoji Tanabe
9. Shengxiang Yang

Papers from Bo D. Wang's perspective

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

1. A review of multiobjective test problems and a scalable test problem toolkit (IEEE Transactions on Evolutionary Computation)
2. Performance assessment of multiobjective optimizers: an analysis and review (IEEE Transactions on Evolutionary Computation)
3. A fast and elitist multiobjective genetic algorithm: NSGA-II
4. Indicator-Based Selection in Multiobjective Search (Parallel Problem Solving from Nature)
5. Simulated Binary Crossover for Continuous Search Space
6. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition (IEEE Transactions on Evolutionary Computation)
7. SPEA2: Improving the strength pareto evolutionary algorithm
8. Scalable multi-objective optimization test problems (Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600))
9. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results (Evolutionary Computation)
10. Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II (IEEE Transactions on Evolutionary Computation)

Their papers

• A New Dominance Relation-Based Evolutionary Algorithm for Many-Objective Optimization (2016) — 666 citations
• Balancing Convergence and Diversity in Decomposition-Based Many-Objective Optimizers (2016) — 380 citations