J. David Schaffer
Impact in
- Computational Theory and Mathematics top 0.1%
- Advanced Multi-Objective Optimization Algorithms
- Artificial Intelligence top 0.2%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Neural Networks and Applications
- Fuzzy Logic and Control Systems
Papers in
-
- Evolutionary Algorithms and Applications 25
- Metaheuristic Optimization Algorithms Research 21
- Neural Networks and Applications 12
- Neural Networks and Reservoir Computing 5
-
- Gene expression and cancer classification 5
- Co-authors
- Larry J. Eshelman (20 shared papers)Richard A. Caruana (7 shared papers)Rajarshi Das (1 shared paper)Darrell Whitley (1 shared paper)Keith E. Mathias (6 shared papers)John J. Grefenstette (1 shared paper)Walker H. Land (16 shared papers)Stephen A. Zahorian (2 shared papers)
- Journals
- Biomicrofluidics (1 paper)International Journal of Intelligent Systems (1 paper)Physica D Nonlinear Phenomena (1 paper)Applied Soft Computing (1 paper)Scientific Reports (1 paper)
- Partner nations
- United StatesFinlandNetherlands
In The Last Decade
J. David Schaffer
68 papers receiving 6.7k citations
J. David Schaffer's Hit Papers
Peers
Comparison fields: 5 of 178
- Computational Theory and Mathematics 2.9k
- Artificial Intelligence 4.3k
- Industrial and Manufacturing Engineering 729
- Management Science and Operations Research 449
- Control and Systems Engineering 782
Countries citing papers authored by J. David Schaffer
This map shows the geographic impact of J. David Schaffer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by J. David Schaffer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. David Schaffer more than expected).
Fields of papers citing papers by J. David Schaffer
This network shows the impact of papers produced by J. David Schaffer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by J. David Schaffer. The network helps show where J. David Schaffer may publish in the future.
Co-authors
The 25 scholars most cited alongside J. David Schaffer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Multiple Objective Optimization with Vector Evaluated Genetic Algorithms Hit paper breakdown → | 1985 | 2173 |
| 2 | Real-Coded Genetic Algorithms and Interval-Schemata Hit paper breakdown → | 1993 | 1326 |
| 3 | Proceedings of the third international conference on Genetic algorithms Hit paper breakdown → | 1989 | 1152 |
| 4 | A study of control parameters affecting online performance of genetic algorithms for function optimization Hit paper breakdown → | 1989 | 733 |
| 5 | 2003 | 307 | |
| 6 | Biases in the crossover landscape | 1989 | 271 |
| 7 | 1991 | 232 | |
| 8 | 1987 | 167 | |
| 9 | 1988 | 156 | |
| 10 | Crossover's Niche | 1993 | 87 |
| 11 | 1990 | 78 | |
| 12 | On Crossover as an Evolutionarily Viable Strategy. | 1991 | 74 |
| 13 | Multi-objective learning via genetic algorithms | 1985 | 72 |
| 14 | 1991 | 65 | |
| 15 | Crossover Operator Biases: Exploiting the Population Distribution. | 1997 | 61 |
| 16 | Convergence Controlled Variation. | 1996 | 39 |
| 17 | 2011 | 30 | |
| 18 | Representation and hidden bias II: eliminating defining length bias in genetic search via shuffle crossover | 1989 | 29 |
| 19 | 2017 | 27 | |
| 20 | 2016 | 25 |
About J. David Schaffer
J. David Schaffer is a scholar working on Artificial Intelligence, Molecular Biology, Cognitive Neuroscience, Electrical and Electronic Engineering and Computational Theory and Mathematics, having authored 70 papers that have together received 7.4k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (25 papers), Metaheuristic Optimization Algorithms Research (21 papers), Neural Networks and Applications (12 papers), Neural dynamics and brain function (8 papers), Advanced Memory and Neural Computing (7 papers), Advanced Multi-Objective Optimization Algorithms (6 papers), Neural Networks and Reservoir Computing (5 papers) and Gene expression and cancer classification (5 papers). The work is most often cited by research in Computational Theory and Mathematics (2.9k citations), Artificial Intelligence (4.3k citations), Industrial and Manufacturing Engineering (729 citations), Management Science and Operations Research (449 citations) and Control and Systems Engineering (782 citations). J. David Schaffer has collaborated with scholars based in United States, Finland and Netherlands. Frequent co-authors include Larry J. Eshelman, Richard A. Caruana, Rajarshi Das, Darrell Whitley, Keith E. Mathias, John J. Grefenstette, Walker H. Land, Stephen A. Zahorian, W. Land and Paul R. Chiarot. Their work appears in journals such as Biomicrofluidics, International Journal of Intelligent Systems, Physica D Nonlinear Phenomena, Applied Soft Computing and Scientific Reports.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.