Johannes Bader

Computational Theory and Mathematics · 2009–2019

A researcher in the Science corpus: 3 papers; trusts 28 researchers and is trusted by 52 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 32 citations into it; #413 of 12,182 by trust here, #1,748 by citations
• Artificial Intelligence — 26 citations into it; #3,331 of 35,345 by trust here, #10,942 by citations
• Information Systems — 13 citations into it
• Software — 11 citations into it
• Management Science and Operations Research — 9 citations into it; #534 of 11,946 by trust here, #2,310 by citations
• Statistics and Probability — 5 citations into it

Whom Johannes Bader trusts overall

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

1. Eckart Zitzler
2. Kalyanmoy Deb
3. Connie M. Borror
4. Philip Hingston
5. Simon Huband
6. Michael T. M. Emmerich
7. Lothar Thiele
8. Joshua D. Knowles
9. Claire Le Goues
10. L. Barone

Who trusts Johannes Bader overall

1. Ye Tian
2. Yanan Sun
3. Xing-yi Zhang
4. Ran Cheng
5. Yaochu Jin
6. Hisao Ishibuchi
7. Gary G. Yen
8. Yuan Yuan
9. Shengxiang Yang
10. Ke Li

Papers from Johannes Bader's perspective

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

1. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results (Evolutionary Computation)
2. Indicator-Based Selection in Multiobjective Search (Parallel Problem Solving from Nature)
3. On metrics for comparing nondominated sets (Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600))
4. Scalable Test Problems for Evolutionary Multiobjective Optimization (Evolutionary Multiobjective Optimization)
5. An EMO Algorithm Using the Hypervolume Measure as Selection Criterion (International Conference on Evolutionary Multi-Criterion Optimization)
6. Multi-objective optimization using evolutionary algorithms
7. A faster algorithm for calculating hypervolume (IEEE Transactions on Evolutionary Computation)
8. Genetic Algorithms in Search
9. Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy (Evolutionary Computation)
10. The Hypervolume Indicator Revisited: On the Design of Pareto-compliant Indicators Via Weighted Integration (International Conference on Evolutionary Multi-Criterion Optimization)

Their papers

• HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization (2011) — 1,992 citations
• Theory of the hypervolume indicator: optimal μ-distributions and the choice of the reference point (2009) — 432 citations
• Getafix: learning to fix bugs automatically (2019) — 271 citations