Patrick M. Reed

Artificial Intelligence · 2001–2017

A researcher in the Science corpus: 11 papers; trusts 42 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 90 citations into it; #12,687 of 35,345 by trust here, #19,018 by citations
• Computational Theory and Mathematics — 86 citations into it; #2,112 of 12,182 by trust here, #3,448 by citations
• Water Science and Technology — 52 citations into it; #1,469 of 1,711 by trust here, #786 by citations
• Environmental Engineering — 51 citations into it
• Ocean Engineering — 40 citations into it; #750 of 3,193 by trust here, #469 by citations
• Global and Planetary Change — 32 citations into it
• Management Science and Operations Research — 28 citations into it
• Civil and Structural Engineering — 21 citations into it; #2,219 of 6,160 by trust here, #2,294 by citations

Whom Patrick M. Reed trusts overall

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

1. Kalyanmoy Deb
2. Eckart Zitzler
3. David E. Goldberg
4. Lothar Thiele
5. John H. Holland
6. Marco Laumanns
7. D. V. Veldhuizen
8. Jasper A. Vrugt
9. Carlos Artemio Coello Coello
10. Joshua D. Knowles

Who trusts Patrick M. Reed overall

1. Joshua B. Kollat
2. David Hadka
3. Himanshu Jain
4. Kalyanmoy Deb
5. Joseph R. Kasprzyk
6. Christian von Lücken
7. Ran Cheng
8. Holger R. Maier
9. K. V. Werkhoven
10. Yaochu Jin

Papers from Patrick M. Reed's perspective

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

1. Genetic Algorithms in Search Optimization and Machine Learning
2. Simulated Binary Crossover for Continuous Search Space
3. Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy (Evolutionary Computation)
4. Performance assessment of multiobjective optimizers: an analysis and review (IEEE Transactions on Evolutionary Computation)
5. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results (Evolutionary Computation)
6. A fast and elitist multiobjective genetic algorithm: NSGA-II
7. Multi-objective optimization using evolutionary algorithms
8. Genetic Algorithms in Search
9. Indicator-Based Selection in Multiobjective Search (Parallel Problem Solving from Nature)
10. No free lunch theorems for optimization

Their papers

• Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework (2013) — 668 citations
• Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design (2005) — 353 citations
• A multiobjective approach to cost effective long-term groundwater monitoring using an elitist nondominated sorted genetic algorithm with historical data (2001) — 100 citations
• Evolutionary multiobjective optimization in water resources: The past, present, and future (2012) — 544 citations
• Many objective robust decision making for complex environmental systems undergoing change (2012) — 499 citations
• The food‐energy‐water nexus: Transforming science for society (2017) — 231 citations
• Battling Arrow’s Paradox to Discover Robust Water Management Alternatives (2016) — 46 citations
• Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions (2014) — 596 citations
• Time‐varying sensitivity analysis clarifies the effects of watershed model formulation on model behavior (2013) — 155 citations
• State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management (2010) — 599 citations
• Sensitivity-guided reduction of parametric dimensionality for multi-objective calibration of watershed models (2009)