Erik D. Goodman

9.3k total citations · 5 hit papers
198 papers, 6.0k citations indexed

About

Erik D. Goodman is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Control and Systems Engineering. According to data from OpenAlex, Erik D. Goodman has authored 198 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 109 papers in Artificial Intelligence, 58 papers in Computational Theory and Mathematics and 27 papers in Control and Systems Engineering. Recurrent topics in Erik D. Goodman's work include Evolutionary Algorithms and Applications (74 papers), Metaheuristic Optimization Algorithms Research (71 papers) and Advanced Multi-Objective Optimization Algorithms (55 papers). Erik D. Goodman is often cited by papers focused on Evolutionary Algorithms and Applications (74 papers), Metaheuristic Optimization Algorithms Research (71 papers) and Advanced Multi-Objective Optimization Algorithms (55 papers). Erik D. Goodman collaborates with scholars based in United States, China and Denmark. Erik D. Goodman's co-authors include William F. Punch, Lihong Xu, Kalyanmoy Deb, Zhun Fan, Michael L. Raymer, Leslie A. Kuhn, Anil K. Jain, Zhichao Lu, Xinye Cai and Wenji Li and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Molecular Biology and Ecology.

In The Last Decade

Erik D. Goodman

188 papers receiving 5.7k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Dimensionality reduction using genetic algorithms

2000 618 citations Michael L. Raymer, William F. Punch et al. profile →
Introduction to genetic algorithms

2009 397 citations Erik D. Goodman profile →
Push and pull search for solving constrained multi-objective optimization problems

2018 372 citations Zhun Fan, Hui Li et al. profile →
NSGA-Net

2019 285 citations Vishnu Naresh Boddeti, Kalyanmoy Deb et al. Proceedings of the Genetic and Evolutionary Computation Conference profile →
An improved epsilon constraint-handling method in MOEA/D for CMOPs with large infeasible regions

2019 272 citations Zhun Fan, Erik D. Goodman et al. profile →

Peers

Erik D. Goodman

CTM

CVPR

CSE

IME

Darrell Whitley United States

Zhang Yon China

Ferrante Neri United Kingdom

Hans-Georg Beyer Austria

Manuel Lozano Spain

Jouni Lampinen Finland

Joaquín Derrac Spain

Kusum Deep India

Shahryar Rahnamayan Canada

Janez Brest Slovenia

Darrell Whitley United States

Erik D. Goodman

3.2k ×1.0

1.2k ×0.6

CTM

559 ×0.7

CVPR

636 ×1.1

CSE

608 ×1.3

IME

Citations per year, relative to Erik D. Goodman Erik D. Goodman (= 1×) peers Darrell Whitley

Countries citing papers authored by Erik D. Goodman

Since Specialization

Citations

This map shows the geographic impact of Erik D. Goodman'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 Erik D. Goodman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erik D. Goodman more than expected).

Fields of papers citing papers by Erik D. Goodman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erik D. Goodman. 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 Erik D. Goodman. The network helps show where Erik D. Goodman may publish in the future.

Co-authorship network of co-authors of Erik D. Goodman

This figure shows the co-authorship network connecting the top 25 collaborators of Erik D. Goodman. A scholar is included among the top collaborators of Erik D. Goodman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Erik D. Goodman. Erik D. Goodman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Saxena, Dhish Kumar, et al.. (2024). Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization. 2 indexed citations

Bao, Chunteng, et al.. (2023). Many-task evolutionary algorithm with adaptive knowledge transfer via density-based clustering. Knowledge-Based Systems. 278. 110906–110906. 2 indexed citations

Guha, Ritam, Wei Ao, Vishnu Naresh Boddeti, et al.. (2023). MOAZ: A Multi-Objective AutoML-Zero Framework. Proceedings of the Genetic and Evolutionary Computation Conference. 485–492. 2 indexed citations

Vega, Francisco Fernández de, Gustavo Olague, Daniel Carlos Ferreira Lanza, et al.. (2020). Time and Individual Duration in Genetic Programming. IEEE Access. 8. 38692–38713. 9 indexed citations

Schwaab, Jonas, Kalyanmoy Deb, Erik D. Goodman, et al.. (2018). Using multi-objective optimization to secure fertile soils across municipalities. Applied Geography. 97. 75–84. 16 indexed citations

Cao, Leilei, Lihong Xu, Erik D. Goodman, Shuwei Zhu, & Hui Li. (2018). A differential prediction model for evolutionary dynamic multiobjective optimization. Proceedings of the Genetic and Evolutionary Computation Conference. 601–608. 8 indexed citations

Schwaab, Jonas, et al.. (2017). How to choose the right planning horizon? Using multi-objective optimization to support urban planning. 1 indexed citations

Goodman, Erik D., et al.. (2015). Optimizing an agent-based traffic evacuation model using genetic algorithms. Winter Simulation Conference. 288–299. 4 indexed citations

Firpi, Hiram, Erik D. Goodman, & Javier Echauz. (2006). On Prediction of Epileptic Seizures by Means of Genetic Programming Artificial Features. Annals of Biomedical Engineering. 34(3). 515–529. 12 indexed citations

10.

Fan, Zhun, Mogens Myrup Andreasen, Jiachuan Wang, Erik D. Goodman, & Lars Hein. (2005). Towards an Evolvable Chromosome Model for Interactive Computer Design Support. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 1861. 1 indexed citations

11.

Hu, Jianjun, et al.. (2002). Adaptive Hierarchical Fair Competition (AHFC) Model For Parallel Evolutionary Algorithms. Genetic and Evolutionary Computation Conference. 772–779. 28 indexed citations

12.

Fan, Zhun, Kisung Seo, Ronald Rosenberg, Jianjun Hu, & Erik D. Goodman. (2002). Exploring Multiple Design Topologies Using Genetic Programming And Bond Graphs. Genetic and Evolutionary Computation Conference. 1073–1080. 6 indexed citations

13.

Hu, Jianjun, et al.. (2002). Structure Fitness Sharing (SFS) for evolutionary design by genetic programming. Genetic and Evolutionary Computation Conference. 780–787. 12 indexed citations

14.

Seo, Kisung, Erik D. Goodman, & Ronald Rosenberg. (2001). First steps toward automated design of mechatronic systems using bond graphs and genetic programming. Genetic and Evolutionary Computation Conference. 189–189. 5 indexed citations

15.

Lin, Shyh-Chang, Erik D. Goodman, & William F. Punch. (1997). A Genetic Algorithm Approach to Dynamic Job Shop Scheduling Problem.. 481–488. 55 indexed citations

16.

Raymer, Michael L., et al.. (1997). Predicting conserved water-mediated and polar ligand interactions in proteins using a K-nearest-neighbors genetic algorithm. Journal of Molecular Biology. 265(4). 445–464. 121 indexed citations

17.

Punch, William F., et al.. (1995). A Standard GA Approach to Native Protein Conformation Prediction. international conference on Genetic algorithms. 574–581. 48 indexed citations

18.

Punch, William F., et al.. (1993). Further Research on Feature Selection and Classification Using Genetic Algorithms. international conference on Genetic algorithms. 557–564. 167 indexed citations

19.

Goodman, Erik D., et al.. (1987). Genetic learning procedures in distributed environments. international conference on Genetic algorithms. 162–169. 11 indexed citations

20.

Johnson, Donn T., et al.. (1980). A Computer Simulation to Maximize Asparagus Yield1. Journal of the American Society for Horticultural Science. 105(1). 37–42. 12 indexed citations

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.

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