Erik D. Goodman

ScholarGPS® ID: 82203995808959

Affiliation
Michigan State University, East Lansing, United States
Affiliation History

Field
Engineering and Computer Science
Discipline
Electrical and Computer Engineering
Top Specialties
Evolutionary Computation | Mathematical Optimization | Genetic Programming | Genetic Algorithm | Multi-objective Optimization | Control Theory | Evolutionary Algorithm | Mechatronics | Soft Computing | Computational Intelligence | Cybernetics | Microelectromechanical Systems | Energy | Robotics | Environment (systems)
Metrics Summary
Publication Count
194
Predicted Citations
6,508
Predicted h-index
41
Ranking

Publications and Citation History

Publications based on Top Specialties

Types of Publication

  • Publications
  • Books
  • Patents
  • NIH/NSF
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An Interactive Knowledge-Based Multiobjective Evolutionary Algorithm Framework for Practical Optimization Problems (journal article)
Ghosh, Abhiroop | Deb, Kalyanmoy | Goodman, Erik | Averill, Ronald
IEEE Transactions on Evolutionary Computation, volume 28, issue 1, pages 223-237 (2024).
10.1109/TEVC.2023.3259339
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Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization (book)
Saxena, Dhish Kumar | Mittal, Sukrit | Deb, Kalyanmoy | Goodman, Erik D.
Springer Nature Singapore (2024)
10.1007/978-981-99-2096-9
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Conclusion and Future Research Directions (book chapter)
In Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Saxena, Dhish Kumar | Mittal, Sukrit | Deb, Kalyanmoy | Goodman, Erik D.
Springer Nature Singapore (2024)
10.1007/978-981-99-2096-9_10
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Learning to Analyze the Pareto-Optimal Front (book chapter)
In Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Saxena, Dhish Kumar | Mittal, Sukrit | Deb, Kalyanmoy | Goodman, Erik D.
Springer Nature Singapore (2024)
10.1007/978-981-99-2096-9_9
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Investigating Innovized Progress Operators with Different ML Methods (book chapter)
In Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Saxena, Dhish Kumar | Mittal, Sukrit | Deb, Kalyanmoy | Goodman, Erik D.
Springer Nature Singapore (2024)
10.1007/978-981-99-2096-9_8
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Learning to Simultaneously Converge and Diversify Better: UIP Operator (book chapter)
In Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Saxena, Dhish Kumar | Mittal, Sukrit | Deb, Kalyanmoy | Goodman, Erik D.
Springer Nature Singapore (2024)
10.1007/978-981-99-2096-9_7
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Learning to Converge Better: IP2 Operator (book chapter)
In Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Saxena, Dhish Kumar | Mittal, Sukrit | Deb, Kalyanmoy | Goodman, Erik D.
Springer Nature Singapore (2024)
10.1007/978-981-99-2096-9_5
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Learning to Diversify Better: IP3 Operator (book chapter)
In Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Saxena, Dhish Kumar | Mittal, Sukrit | Deb, Kalyanmoy | Goodman, Erik D.
Springer Nature Singapore (2024)
10.1007/978-981-99-2096-9_6
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Learning to Understand the Problem Structure (book chapter)
In Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Saxena, Dhish Kumar | Mittal, Sukrit | Deb, Kalyanmoy | Goodman, Erik D.
Springer Nature Singapore (2024)
10.1007/978-981-99-2096-9_4
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Foundational Studies on ML-Based Enhancements (book chapter)
In Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Saxena, Dhish Kumar | Mittal, Sukrit | Deb, Kalyanmoy | Goodman, Erik D.
Springer Nature Singapore (2024)
10.1007/978-981-99-2096-9_3
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Optimization Problems and Algorithms (book chapter)
In Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Saxena, Dhish Kumar | Mittal, Sukrit | Deb, Kalyanmoy | Goodman, Erik D.
Springer Nature Singapore (2024)
10.1007/978-981-99-2096-9_2
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A Unified Innovized Progress Operator for Performance Enhancement in Evolutionary Multi- and Many-objective Optimization (journal article)
Mittal, Sukrit | Saxena, Dhish Kumar | Deb, Kalyanmoy | Goodman, Erik D.
IEEE Transactions on Evolutionary Computation (2024).
10.1109/TEVC.2023.3321603
Cited by (2) | Cite | Source
A user-guided innovization -based evolutionary algorithm framework for practical multi-objective optimization problems (journal article)
Ghosh, Abhiroop | Deb, Kalyanmoy | Goodman, Erik | Averill, Ronald
Engineering Optimization, volume 55, issue 12, pages 2084-2096 (2023).
10.1080/0305215X.2022.2144275
Cited by (4) | Cite | Source
Many-task evolutionary algorithm with adaptive knowledge transfer via density-based clustering (journal article)
Bao, Chunteng | Gao, Diju | Ding, Yi | Xu, Lihong | Goodman, Erik D.
Knowledge-Based Systems, volume 278 (2023).
10.1016/j.knosys.2023.110906
Cited by (1) | Cite | Source
MOAZ: A Multi-Objective AutoML-Zero Framework (conference)
Guha, Ritam | Ao, Wei | Kelly, Stephen | Boddeti, Vishnu | Goodman, Erik | Banzhaf, Wolfgang | Deb, Kalyanmoy
GECCO '23: Genetic and Evolutionary Computation Conference (2023)
Lisbon Portugal
10.1145/3583131.3590391
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A general framework for enhancing relaxed Pareto dominance methods in evolutionary many-objective optimization (journal article)
Zhu, Shuwei | Xu, Lihong | Goodman, Erik | Deb, Kalyanmoy | Lu, Zhichao
Natural Computing, volume 22, issue 2, pages 287-313 (2023).
10.1007/s11047-022-09889-z
Cited by (4) | Cite | Source
Interview: Kalyanmoy Deb Talks about Formation, Development and Challenges of the EMO Community, Important Positions in His Career, and Issues Faced Getting His Works Published (journal article)
Coello, Carlos | Goodman, Erik | Miettinen, Kaisa | Saxena, Dhish | Schütze, Oliver | Thiele, Lothar
Mathematical and Computational Applications, volume 28, issue 2, pages 34- (2023).
10.3390/mca28020034
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IK-EMOViz: An Interactive Knowledge-Based Evolutionary Multi-objective Optimization Framework (book chapter)
In Evolutionary Multi-Criterion Optimization
Ghosh, Abhiroop | Deb, Kalyanmoy | Averill, Ronald | Goodman, Erik
Springer Nature Switzerland (2023)
10.1007/978-3-031-27250-9_43
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Enhanced Innovized Progress Operator for Evolutionary Multi- and Many-Objective Optimization (journal article)
Mittal, Sukrit | Saxena, Dhish Kumar | Deb, Kalyanmoy | Goodman, Erik D.
IEEE Transactions on Evolutionary Computation, volume 26, issue 5, pages 961-975 (2022).
10.1109/TEVC.2021.3131952
Cited by (18) | Cite | Source
Hierarchical Topology-Based Cluster Representation for Scalable Evolutionary Multiobjective Clustering (journal article)
Zhu, Shuwei | Xu, Lihong | Goodman, Erik D.
IEEE Transactions on Cybernetics, volume 52, issue 9, pages 9846-9860 (2022).
10.1109/TCYB.2021.3081988
Cited by (14) | Cite | Source