Tushar Goel

Computational Theory and Mathematics · 2001–2009

A researcher in the Science corpus: 7 papers; trusts 12 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 34 citations into it; #2,261 of 12,182 by trust here, #2,489 by citations
• Management Science and Operations Research — 22 citations into it; #5,290 of 11,946 by trust here, #4,921 by citations
• Statistics and Probability — 18 citations into it; #6,477 of 12,932 by trust here, #7,165 by citations
• Artificial Intelligence — 17 citations into it; #11,887 of 35,345 by trust here, #22,463 by citations

Whom Tushar Goel trusts overall

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

1. Kalyanmoy Deb
2. Néstor V. Queipo
3. Timothy W. Simpson
4. Jack P. C. Kleijnen
5. Raphael T. Haftka
6. Joshua D. Knowles
7. Donald R. Jones
8. Anil K. Jain
9. Stephen J. Leary
10. Martin Meckesheimer

Who trusts Tushar Goel overall

1. Felipe Antonio Chegury Viana
2. Ki-Don Lee
3. Kwang‐Yong Kim
4. Yaochu Jin
5. Raphael T. Haftka
6. Ali Mehmani
7. Alexander I. J. Forrester
8. Handing Wang
9. Erdem Acar
10. Thomas Bartz-Beielstein

Papers from Tushar Goel's perspective

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

1. Computationally Inexpensive Metamodel Assessment Strategies
2. Genetic Algorithms in Search
3. Efficient Global Optimization of Expensive Black-Box Functions
4. Multi-objective optimization using evolutionary algorithms
5. A rigorous framework for optimization of expensive functions by surrogates
6. Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling (IEEE Transactions on Evolutionary Computation)
7. ParEGO: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems (IEEE Transactions on Evolutionary Computation)
8. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code
9. Algorithms for Clustering Data
10. Sampling Strategies for Computer Experiments: Design and Analysis

Their papers

• Controlled Elitist Non-dominated Sorting Genetic Algorithms for Better Convergence (2001) — 490 citations
• Comparing error estimation measures for polynomial and kriging approximation of noise-free functions (2009) — 101 citations
• Multiple Surrogates for the Shape Optimization of Bluff Body-Facilitated Mixing (2005) — 49 citations
• Pitfalls of using a single criterion for selecting experimental designs (2008) — 64 citations
• Response surface approximation of pareto optimal front in multi-objective optimization (2004) — 347 citations
• Ensemble of surrogates (2007) — 729 citations
• Surrogate-based Analysis and Optimization (2005)