Ryoji Tanabe

Computational Theory and Mathematics · 2013–2020

A researcher in the Science corpus: 3 papers; trusts 63 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 44 citations into it; #1,159 of 12,182 by trust here, #3,033 by citations
• Artificial Intelligence — 40 citations into it; #5,908 of 35,345 by trust here, #15,236 by citations
• Management Science and Operations Research — 6 citations into it

Whom Ryoji Tanabe trusts overall

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

1. Kalyanmoy Deb
2. Eckart Zitzler
3. Ponnuthurai Nagaratnam Suganthan
4. Janez Brest
5. Jingqiao Zhang
6. Qingfu Zhang
7. Tapabrata Ray
8. Carlos Artemio Coello Coello
9. A. K. Qin
10. Yong Wang

Who trusts Ryoji Tanabe overall

1. Swagatam Das
2. Noor H. Awad
3. Ponnuthurai Nagaratnam Suganthan
4. Ali Wagdy Mohamed
5. Janez Brest
6. Guohua Wu
7. Sankha Subhra Mullick
8. Mostafa Z. Ali
9. Sam Daulton
10. Armin Cheraghalipour

Papers from Ryoji Tanabe's perspective

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

1. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results (Evolutionary Computation)
2. A fast and elitist multiobjective genetic algorithm: NSGA-II
3. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
4. Multi-objective optimization using evolutionary algorithms
5. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition (IEEE Transactions on Evolutionary Computation)
6. Indicator-Based Selection in Multiobjective Search (Parallel Problem Solving from Nature)
7. Scalable Test Problems for Evolutionary Multiobjective Optimization (Evolutionary Multiobjective Optimization)
8. Simulated Binary Crossover for Continuous Search Space
9. A review of multiobjective test problems and a scalable test problem toolkit (IEEE Transactions on Evolutionary Computation)
10. Performance assessment of multiobjective optimizers: an analysis and review (IEEE Transactions on Evolutionary Computation)

Their papers

• Success-history based parameter adaptation for Differential Evolution (2013) — 1,310 citations
• Improving the search performance of SHADE using linear population size reduction (2014) — 1,554 citations
• An easy-to-use real-world multi-objective optimization problem suite (2020) — 329 citations