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ORCIDErik D. Goodman
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- affiliation: Michigan State University, East Lansing, MI, USA
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2020 – today
- 2024
[b1]Dhish Kumar Saxena, Sukrit Mittal
, Kalyanmoy Deb, Erik D. Goodman:
Machine Learning Assisted Evolutionary Multi- and Many-Objective Optimization. Springer 2024, ISBN 978-981-99-2095-2, pp. 1-239- [j68]Abhiroop Ghosh, Kalyanmoy Deb, Erik D. Goodman, Ronald C. Averill:
An Interactive Knowledge-Based Multiobjective Evolutionary Algorithm Framework for Practical Optimization Problems. IEEE Trans. Evol. Comput. 28(1): 223-237 (2024) - 2023
- [j67]Chunteng Bao, Diju Gao, Wei Gu, Lihong Xu, Erik D. Goodman:
A new adaptive decomposition-based evolutionary algorithm for multi- and many-objective optimization. Expert Syst. Appl. 213(Part): 119080 (2023) - [j66]Chunteng Bao, Diju Gao, Yi Ding, Lihong Xu, Erik D. Goodman:
Many-task evolutionary algorithm with adaptive knowledge transfer via density-based clustering. Knowl. Based Syst. 278: 110906 (2023) - [j65]Shuwei Zhu, Lihong Xu, Erik D. Goodman, Kalyanmoy Deb, Zhichao Lu:
A general framework for enhancing relaxed Pareto dominance methods in evolutionary many-objective optimization. Nat. Comput. 22(2): 287-313 (2023) - [c88]Abhiroop Ghosh, Kalyanmoy Deb, Ronald C. Averill, Erik D. Goodman:
IK-EMOViz: An Interactive Knowledge-Based Evolutionary Multi-objective Optimization Framework. EMO 2023: 606-619 - [c87]Ritam Guha, Wei Ao, Stephen Kelly, Vishnu Boddeti, Erik D. Goodman, Wolfgang Banzhaf, Kalyanmoy Deb:
MOAZ: A Multi-Objective AutoML-Zero Framework. GECCO 2023: 485-492 - 2022
- [j64]Chaoda Peng, Hai-Lin Liu, Erik D. Goodman, Kay Chen Tan:
A two-phase framework of locating the reference point for decomposition-based constrained multi-objective evolutionary algorithms. Knowl. Based Syst. 239: 107933 (2022) - [j63]Yuanping Su, Lihong Xu, Erik D. Goodman:
Hybrid Surrogate-Based Constrained Optimization With a New Constraint-Handling Method. IEEE Trans. Cybern. 52(6): 5394-5407 (2022) - [j62]Shuwei Zhu, Lihong Xu, Erik D. Goodman, Zhichao Lu:
A New Many-Objective Evolutionary Algorithm Based on Generalized Pareto Dominance. IEEE Trans. Cybern. 52(8): 7776-7790 (2022) - [j61]Shuwei Zhu, Lihong Xu, Erik D. Goodman:
Hierarchical Topology-Based Cluster Representation for Scalable Evolutionary Multiobjective Clustering. IEEE Trans. Cybern. 52(9): 9846-9860 (2022) - [j60]Sukrit Mittal, Dhish Kumar Saxena, Kalyanmoy Deb, Erik D. Goodman:
Enhanced Innovized Progress Operator for Evolutionary Multi- and Many-Objective Optimization. IEEE Trans. Evol. Comput. 26(5): 961-975 (2022) - [j59]Sukrit Mittal, Dhish Kumar Saxena, Kalyanmoy Deb, Erik D. Goodman:
A Learning-based Innovized Progress Operator for Faster Convergence in Evolutionary Multi-objective Optimization. ACM Trans. Evol. Learn. Optim. 2(1): 1:1-1:29 (2022) - [i15]Abhiroop Ghosh, Kalyanmoy Deb, Erik D. Goodman, Ronald C. Averill:
An Interactive Knowledge-based Multi-objective Evolutionary Algorithm Framework for Practical Optimization Problems. CoRR abs/2209.08604 (2022) - 2021
- [j58]Zhichao Lu, Gautam Sreekumar, Erik D. Goodman, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti:
Neural Architecture Transfer. IEEE Trans. Pattern Anal. Mach. Intell. 43(9): 2971-2989 (2021) - [j57]Chaoda Peng, Hai-Lin Liu, Erik D. Goodman:
A Cooperative Evolutionary Framework Based on an Improved Version of Directed Weight Vectors for Constrained Multiobjective Optimization With Deceptive Constraints. IEEE Trans. Cybern. 51(11): 5546-5558 (2021) - [j56]Zhichao Lu, Ian Whalen, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti:
Multiobjective Evolutionary Design of Deep Convolutional Neural Networks for Image Classification. IEEE Trans. Evol. Comput. 25(2): 277-291 (2021) - [c86]Kalyanmoy Deb, Sukrit Mittal, Dhish Kumar Saxena, Erik D. Goodman:
Embedding a Repair Operator in Evolutionary Single and Multi-objective Algorithms - An Exploitation-Exploration Perspective. EMO 2021: 89-101 - [c85]Abhiroop Ghosh, Kalyanmoy Deb, Ronald C. Averill, Erik D. Goodman:
Combining User Knowledge and Online Innovization for Faster Solution to Multi-objective Design Optimization Problems. EMO 2021: 102-114 - [c84]Shuwei Zhu, Lihong Xu, Erik D. Goodman, Kalyanmoy Deb, Zhichao Lu:
The (M-1)+1 Framework of Relaxed Pareto Dominance for Evolutionary Many-Objective Optimization. EMO 2021: 349-361 - 2020
- [j55]Francisco Fernández de Vega, Gustavo Olague, Daniel Lanza, Francisco Chávez de la O, Wolfgang Banzhaf, Erik D. Goodman, Jose Menendez-Clavijo, Axel Martinez:
Time and Individual Duration in Genetic Programming. IEEE Access 8: 38692-38713 (2020) - [j54]Zhun Fan, Wenji Li, Xinye Cai, Hui Li, Caimin Wei, Qingfu Zhang, Kalyanmoy Deb, Erik D. Goodman:
Difficulty Adjustable and Scalable Constrained Multiobjective Test Problem Toolkit. Evol. Comput. 28(3): 339-378 (2020) - [j53]Shuwei Zhu, Lihong Xu, Erik D. Goodman:
Evolutionary multi-objective automatic clustering enhanced with quality metrics and ensemble strategy. Knowl. Based Syst. 188 (2020) - [j52]Matt Ryerkerk, Ronald C. Averill, Kalyanmoy Deb, Erik D. Goodman:
A novel selection mechanism for evolutionary algorithms with metameric variable-length representations. Soft Comput. 24(21): 16439-16452 (2020) - [j51]Chaoda Peng, Hai-Lin Liu, Erik D. Goodman:
Handling multi-objective optimization problems with unbalanced constraints and their effects on evolutionary algorithm performance. Swarm Evol. Comput. 55: 100676 (2020) - [j50]Leilei Cao, Lihong Xu, Erik D. Goodman, Chunteng Bao, Shuwei Zhu:
Evolutionary Dynamic Multiobjective Optimization Assisted by a Support Vector Regression Predictor. IEEE Trans. Evol. Comput. 24(2): 305-319 (2020) - [c83]Abhiroop Ghosh, Erik D. Goodman, Kalyanmoy Deb, Ronald C. Averill, Alejandro Diaz:
A Large-scale Bi-objective Optimization of Solid Rocket Motors Using Innovization. CEC 2020: 1-8 - [c82]Zhichao Lu, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti:
NSGANetV2: Evolutionary Multi-objective Surrogate-Assisted Neural Architecture Search. ECCV (1) 2020: 35-51 - [c81]Zhichao Lu, Ian Whalen, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti:
NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm (Extended Abstract). IJCAI 2020: 4750-4754 - [e3]Wolfgang Banzhaf, Erik D. Goodman, Leigh Sheneman, Leonardo Trujillo, Bill Worzel:
Genetic Programming Theory and Practice XVII [GPTP 2019, Michigan State University, East Lansing, Michigan, USA, May 16-19, 2019]. Springer 2020, ISBN 978-3-030-39957-3 [contents] - [i14]Francisco Fernández de Vega, Gustavo Olague, Francisco Chávez de la O, Daniel Lanza, Wolfgang Banzhaf, Erik D. Goodman:
It is Time for New Perspectives on How to Fight Bloat in GP. CoRR abs/2005.00603 (2020) - [i13]Zhichao Lu, Gautam Sreekumar, Erik D. Goodman, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti:
Neural Architecture Transfer. CoRR abs/2005.05859 (2020) - [i12]Zhichao Lu, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti:
NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search. CoRR abs/2007.10396 (2020) - [i11]Sukrit Mittal, Dhish Kumar Saxena, Kalyanmoy Deb, Erik D. Goodman:
Enhanced Innovized Repair Operator for Evolutionary Multi- and Many-objective Optimization. CoRR abs/2011.10760 (2020)
2010 – 2019
- 2019
- [j49]Zhun Fan, Yi Fang, Wenji Li, Xinye Cai, Caimin Wei, Erik D. Goodman:
MOEA/D with angle-based constrained dominance principle for constrained multi-objective optimization problems. Appl. Soft Comput. 74: 621-633 (2019) - [j48]Leilei Cao, Lihong Xu, Erik D. Goodman, Hui Li:
Decomposition-based evolutionary dynamic multiobjective optimization using a difference model. Appl. Soft Comput. 76: 473-490 (2019) - [j47]Yifan Li, Hai-Lin Liu, Erik D. Goodman:
Hyperplane-Approximation-Based Method for Many-Objective Optimization Problems with Redundant Objectives. Evol. Comput. 27(2): 313-344 (2019) - [j46]Leilei Cao, Lihong Xu, Erik D. Goodman:
A collaboration-based particle swarm optimizer with history-guided estimation for optimization in dynamic environments. Expert Syst. Appl. 120: 1-13 (2019) - [j45]Chunteng Bao, Lihong Xu, Erik D. Goodman:
A new dominance-relation metric balancing convergence and diversity in multi- and many-objective optimization. Expert Syst. Appl. 134: 14-27 (2019) - [j44]Matt Ryerkerk, Ronald C. Averill, Kalyanmoy Deb, Erik D. Goodman:
A survey of evolutionary algorithms using metameric representations. Genet. Program. Evolvable Mach. 20(4): 441-478 (2019) - [j43]Chunteng Bao, Lihong Xu, Erik D. Goodman:
A novel two-archive matching-based algorithm for multi- and many-objective optimization. Inf. Sci. 497: 106-128 (2019) - [j42]Leilei Cao, Lihong Xu, Erik D. Goodman:
A collaboration-based particle swarm optimizer for global optimization problems. Int. J. Mach. Learn. Cybern. 10(6): 1279-1300 (2019) - [j41]Zhun Fan, Wenji Li, Xinye Cai, Han Huang, Yi Fang, Yugen You, Jiajie Mo, Caimin Wei, Erik D. Goodman:
An improved epsilon constraint-handling method in MOEA/D for CMOPs with large infeasible regions. Soft Comput. 23(23): 12491-12510 (2019) - [j40]Zhun Fan, Wenji Li, Xinye Cai, Hui Li, Caimin Wei, Qingfu Zhang, Kalyanmoy Deb, Erik D. Goodman:
Push and pull search for solving constrained multi-objective optimization problems. Swarm Evol. Comput. 44: 665-679 (2019) - [j39]Zhun Fan, Yugen You, Xinye Cai, Haodong Zheng, Guijie Zhu, Wenji Li, Akhil Garg, Kalyanmoy Deb, Erik D. Goodman:
Analysis and multi-objective optimization of a kind of teaching manipulator. Swarm Evol. Comput. 50 (2019) - [c80]Zhichao Lu, Ian Whalen, Vishnu Boddeti, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf:
NSGA-Net: neural architecture search using multi-objective genetic algorithm. GECCO 2019: 419-427 - [c79]Francisco Fernández de Vega, Gustavo Olague, Francisco Chávez de la O, Daniel Lanza, Wolfgang Banzhaf, Erik D. Goodman:
It Is Time for New Perspectives on How to Fight Bloat in GP. GPTP 2019: 25-38 - [c78]Chaoda Peng, Hai-Lin Liu, Erik D. Goodman:
Investigating the Performance of Evolutionary Algorithms on Constrained Multi-objective Optimization Problems with Deceptive Infeasible Regions. SSCI 2019: 3047-3052 - [e2]Kalyanmoy Deb, Erik D. Goodman, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, Patrick M. Reed:
Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings. Lecture Notes in Computer Science 11411, Springer 2019, ISBN 978-3-030-12597-4 [contents] - [i10]Zhichao Lu, Ian Whalen, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti:
Multi-Criterion Evolutionary Design of Deep Convolutional Neural Networks. CoRR abs/1912.01369 (2019) - 2018
- [j38]Jonas Schwaab, Kalyanmoy Deb, Erik D. Goodman, Sven Lautenbach, Maarten van Strien, Adrienne Grêt-Regamey:
Improving the performance of genetic algorithms for land-use allocation problems. Int. J. Geogr. Inf. Sci. 32(5): 907-930 (2018) - [j37]Yuanping Su, Lihong Xu, Erik D. Goodman:
Control allocation-based adaptive control for greenhouse climate. Int. J. Syst. Sci. 49(6): 1146-1163 (2018) - [j36]Leilei Cao, Lihong Xu, Erik D. Goodman:
A neighbor-based learning particle swarm optimizer with short-term and long-term memory for dynamic optimization problems. Inf. Sci. 453: 463-485 (2018) - [j35]Erik D. Goodman:
The Path to DevOps. IEEE Softw. 35(5): 71-75 (2018) - [j34]Zhun Fan, Jiewei Lu, Maoguo Gong, Honghui Xie, Erik D. Goodman:
Automatic Tobacco Plant Detection in UAV Images via Deep Neural Networks. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 11(3): 876-887 (2018) - [c77]José R. Llera, Erik D. Goodman, Erik S. Runkle, Lihong Xu:
Improving greenhouse environmental control using crop-model-driven multi-objective optimization. GECCO (Companion) 2018: 292-293 - [c76]Leilei Cao, Lihong Xu, Erik D. Goodman, Shuwei Zhu, Hui Li:
A differential prediction model for evolutionary dynamic multiobjective optimization. GECCO 2018: 601-608 - [c75]José R. Llera, Kalyanmoy Deb, Erik S. Runkle, Lihong Xu, Erik D. Goodman:
Evolving and Comparing Greenhouse Control Strategies using Model-Based Multi-Objective Optimization. SSCI 2018: 1929-1936 - [i9]Zhun Fan, Yugen You, Haodong Zheng, Guijie Zhu, Wenji Li, Shen Chen, Kalyanmoy Deb, Erik D. Goodman:
Modeling and Multi-objective Optimization of a Kind of Teaching Manipulator. CoRR abs/1801.10599 (2018) - [i8]Zhun Fan, Yi Fang, Wenji Li, Xinye Cai, Caimin Wei, Erik D. Goodman:
MOEA/D with Angle-based Constrained Dominance Principle for Constrained Multi-objective Optimization Problems. CoRR abs/1802.03608 (2018) - [i7]Zhun Fan, Jiewei Lu, Ce Zheng, Jingan Feng, Longtao Huang, Wenji Li, Erik D. Goodman:
Automated Strabismus Detection based on Deep neural networks for Telemedicine Applications. CoRR abs/1809.02940 (2018) - [i6]Zhichao Lu, Ian Whalen, Vishnu Boddeti, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf:
NSGA-NET: A Multi-Objective Genetic Algorithm for Neural Architecture Search. CoRR abs/1810.03522 (2018) - [i5]Zhun Fan, Wenji Li, Zhaojun Wang, Yutong Yuan, Fuzan Sun, Zhi Yang, Jie Ruan, Zhaocheng Li, Erik D. Goodman:
Embedding Push and Pull Search in the Framework of Differential Evolution for Solving Constrained Single-objective Optimization Problems. CoRR abs/1812.06381 (2018) - 2017
- [j33]Lei Chen, Hai-Lin Liu, Zhun Fan, Shengli Xie, Erik D. Goodman:
Modeling the Tracking Area Planning Problem Using an Evolutionary Multi-Objective Algorithm. IEEE Comput. Intell. Mag. 12(1): 29-41 (2017) - [j32]Matthew L. Ryerkerk, Ronald C. Averill, Kalyanmoy Deb, Erik D. Goodman:
Solving metameric variable-length optimization problems using genetic algorithms. Genet. Program. Evolvable Mach. 18(2): 247-277 (2017) - [j31]Chunteng Bao, Lihong Xu, Erik D. Goodman, Leilei Cao:
A novel non-dominated sorting algorithm for evolutionary multi-objective optimization. J. Comput. Sci. 23: 31-43 (2017) - [j30]Xinye Cai, Xin Cheng, Zhun Fan, Erik D. Goodman, Lisong Wang:
An adaptive memetic framework for multi-objective combinatorial optimization problems: studies on software next release and travelling salesman problems. Soft Comput. 21(9): 2215-2236 (2017) - [j29]Hai-Lin Liu, Lei Chen, Kalyanmoy Deb, Erik D. Goodman:
Investigating the Effect of Imbalance Between Convergence and Diversity in Evolutionary Multiobjective Algorithms. IEEE Trans. Evol. Comput. 21(3): 408-425 (2017) - [j28]Jonas Schwaab, Kalyanmoy Deb, Erik D. Goodman, Sven Lautenbach, Maarten van Strien, Adrienne Grêt-Regamey:
Reducing the loss of agricultural productivity due to compact urban development in municipalities of Switzerland. Comput. Environ. Urban Syst. 65: 162-177 (2017) - [c74]Daniel J. Couvertier, Erik D. Goodman, Kalyanmoy Deb:
Towards an epigenetics-inspired control system for power dispatch problem. GECCO (Companion) 2017: 147-148 - [c73]Jonas Schwaab, Kalyanmoy Deb, Erik D. Goodman, Sven Lautenbach, Maarten van Strien, Adrienne Grêt-Regamey:
Short versus long-term urban planning using multi-objective optimization. GECCO (Companion) 2017: 305-306 - [c72]Zhichao Lu, Kalyanmoy Deb, Erik D. Goodman, John M. Wassick:
Solving a supply-chain management problem using a bilevel approach. GECCO 2017: 1185-1192 - [c71]Leilei Cao, Lihong Xu, Erik D. Goodman, Hui Li:
A First-Order Difference Model-Based Evolutionary Dynamic Multiobjective Optimization. SEAL 2017: 644-655 - [i4]Zhun Fan, Wenji Li, Xinye Cai, Han Huang, Yi Fang, Yugen You, Jiajie Mo, Caimin Wei, Erik D. Goodman:
An Improved Epsilon Constraint-handling Method in MOEA/D for CMOPs with Large Infeasible Regions. CoRR abs/1707.08767 (2017) - [i3]Zhun Fan, Wenji Li, Xinye Cai, Hui Li, Caimin Wei, Qingfu Zhang, Kalyanmoy Deb, Erik D. Goodman:
Push and Pull Search for Solving Constrained Multi-objective Optimization Problems. CoRR abs/1709.05915 (2017) - 2016
- [j27]Leilei Cao, Lihong Xu, Erik D. Goodman:
A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems. Comput. Intell. Neurosci. 2016: 2565809:1-2565809:10 (2016) - [j26]Chenwen Zhu, Lihong Xu, Erik D. Goodman:
Generalization of Pareto-Optimality for Many-Objective Evolutionary Optimization. IEEE Trans. Evol. Comput. 20(2): 299-315 (2016) - [i2]Zhun Fan, Wenji Li, Xinye Cai, Hui Li, Kaiwen Hu, Qingfu Zhang, Kalyanmoy Deb, Erik D. Goodman:
Difficulty Adjustable and Scalable Constrained Multi-objective Test Problem Toolkit. CoRR abs/1612.07603 (2016) - 2015
- [j25]Jean-François Dupuis, Zhun Fan, Erik D. Goodman:
Evolutionary design of discrete controllers for hybrid mechatronic systems. Int. J. Syst. Sci. 46(2): 303-316 (2015) - [j24]Dawei Li, Lihong Xu, Chengxiang Tan, Erik D. Goodman, Daichang Fu, Longjiao Xin:
Digitization and Visualization of Greenhouse Tomato Plants in Indoor Environments. Sensors 15(2): 4019-4051 (2015) - [c70]Zhun Fan, Han Huang, Wenji Li, Shuxiang Xie, Xinye Cai, Erik D. Goodman:
An opposition-based repair operator for multi-objective evolutionary algorithm in constrained optimization problems. ICNC 2015: 330-336 - [c69]Matthew Durak, Nicholas Durak, Erik D. Goodman, Robert Till:
Optimizing an agent-based traffic evacuation model using genetic algorithms. WSC 2015: 288-299 - [i1]Zhun Fan, Wenji Li, Xinye Cai, Huibiao Lin, Shuxiang Xie, Erik D. Goodman:
A New Repair Operator for Multi-objective Evolutionary Algorithm in Constrained Optimization Problems. CoRR abs/1504.00154 (2015) - 2014
- [j23]Dawei Li, Lihong Xu, Erik D. Goodman:
On-line EM Variants for Multivariate Normal Mixture Model in Background Learning and Moving Foreground Detection. J. Math. Imaging Vis. 48(1): 114-133 (2014) - [j22]Haigen Hu, Lihong Xu, Erik D. Goodman, Songwei Zeng:
NSGA-II-based nonlinear PID controller tuning of greenhouse climate for reducing costs and improving performances. Neural Comput. Appl. 24(3-4): 927-936 (2014) - [c68]Jinyao Yan, John R. Deller Jr., Meng Yao, Erik D. Goodman:
Evolutionary model selection for identification of nonlinear parametric systems. ChinaSIP 2014: 693-697 - [c67]Erik D. Goodman:
Introduction to genetic algorithms. GECCO (Companion) 2014: 205-226 - [c66]Blair D. Fleet, Jinyao Yan, David B. Knoester, Meng Yao, John R. Deller Jr., Erik D. Goodman:
Breast Cancer Detection Using Haralick Features of Images Reconstructed from Ultra Wideband Microwave Scans. CLIP@MICCAI 2014: 9-16 - 2013
- [j21]Dawei Li, Lihong Xu, Erik D. Goodman, Yuan Xu, Yang Wu:
Integrating a statistical background- foreground extraction algorithm and SVM classifier for pedestrian detection and tracking. Integr. Comput. Aided Eng. 20(3): 201-216 (2013) - [j20]Zhenhua Li, Erik D. Goodman:
Practical Search Index as a Hardness Measure for Genetic Algorithms. J. Comput. 8(8): 2034-2041 (2013) - [j19]Guojing Fan, Erik D. Goodman, Zhijun Liu:
AHP (Analytic Hierarchy Process) and Computer Analysis Software Used in Tourism Safety. J. Softw. 8(12): 3114-3119 (2013) - [j18]Dawei Li, Lihong Xu, Erik D. Goodman:
Illumination-Robust Foreground Detection in a Video Surveillance System. IEEE Trans. Circuits Syst. Video Technol. 23(10): 1637-1650 (2013) - [c65]Jinyao Yan, John R. Deller Jr., Blair D. Fleet, Erik D. Goodman, Meng Yao:
Evolutionary identification of nonlinear parametric models with a set-theoretic fitness criterion. ChinaSIP 2013: 44-48 - [c64]Erik D. Goodman:
Introduction to genetic algorithms. GECCO (Companion) 2013: 225-246 - 2012
- [j17]Jean-François Dupuis, Zhun Fan, Erik D. Goodman:
Evolutionary Design of Both Topologies and Parameters of a Hybrid Dynamical System. IEEE Trans. Evol. Comput. 16(3): 391-405 (2012) - [c63]Oliver Chikumbo, Erik D. Goodman, Kalyanmoy Deb:
Approximating a multi-dimensional Pareto front for a land use management problem: A modified MOEA with an epigenetic silencing metaphor. IEEE Congress on Evolutionary Computation 2012: 1-9 - [c62]Erik D. Goodman:
Introduction to genetic algorithms. GECCO (Companion) 2012: 671-692 - [c61]Matt Ryerkerk, Ronald C. Averill, Kalyanmoy Deb, Erik D. Goodman:
Meaningful representation and recombination of variable length genomes. GECCO (Companion) 2012: 1471-1472 - [c60]Dawei Li, Lihong Xu, Erik D. Goodman:
Real-Time Statistical Background Learning for Foreground Detection under Unstable Illuminations. ICMLA (1) 2012: 468-472 - 2011
- [c59]Erik D. Goodman:
Introduction to genetic algorithms. GECCO (Companion) 2011: 839-860 - 2010
- [j16]Kisung Seo, Soohwan Hyun, Erik D. Goodman:
Genetic Programming-Based Automatic Gait Generation in Joint Space for a Quadruped Robot. Adv. Robotics 24(15): 2199-2214 (2010) - [c58]Prakarn Unachak, Erik D. Goodman:
Solving multiobjective flexible job-shop scheduling using an adaptive representation. GECCO 2010: 737-742 - [c57]Haigen Hu, Lihong Xu, Erik D. Goodman:
A control optimization algorithm for greenhouse climate control problems. GECCO (Companion) 2010: 2081-2082 - [c56]Erik D. Goodman:
Introduction to genetic algorithms. GECCO (Companion) 2010: 2121-2136 - [c55]Dawei Li, Lihong Xu, Erik D. Goodman:
Online background learning for illumination-robust foreground detection. ICARCV 2010: 1093-1100
2000 – 2009
- 2009
- [c54]Jean-François Dupuis, Zhun Fan, Erik D. Goodman:
Evolved finite state controller for hybrid system. GEC Summit 2009: 105-112 - [c53]Qingsong Hu, Lihong Xu, Erik D. Goodman:
Non-even spread NSGA-II and its application to conflicting multi-objective compatible control. GEC Summit 2009: 223-230 - [c52]Jinchao Liu, Zhun Fan, Erik D. Goodman:
SRDE: an improved differential evolution based on stochastic ranking. GEC Summit 2009: 345-352 - [c51]Prakarn Unachak, Erik D. Goodman:
Adaptive representation for flexible job-shop scheduling and rescheduling. GEC Summit 2009: 511-516 - [c50]Lihong Xu, Bingkun Zhu, Erik D. Goodman:
An improved MOCC with feedback control structure based on preference. GEC Summit 2009: 651-656 - [c49]John C. Oliva, Erik D. Goodman:
Evolutionary search and convertible agents for the simultaneous type and dimensional synthesis of planar mechanisms. GECCO 2009: 1577-1584 - [c48]Jinchao Liu, Zhun Fan, Erik D. Goodman:
SRaDE: an adaptive differential evolution based on stochastic ranking. GECCO 2009: 1871-1872 - [c47]Qingsong Hu, Lihong Xu, Erik D. Goodman:
Dynamic multi-objective control of IPMCs propelled robot fish based on NSGA-II. GECCO 2009: 1927-1928 - [c46]Kisung Seo, Soohwan Hyun, Erik D. Goodman:
Tree-structure-aware GP operators for automatic gait generation of quadruped robot. GECCO (Companion) 2009: 2155-2160 - [c45]Ping Wu, Erik D. Goodman, Tang Jiang, Min Pei:
A hybrid GA-based fuzzy classifying approach to urinary analysis modeling. GECCO (Companion) 2009: 2671-2678 - [c44]Erik D. Goodman:
Introduction to genetic algorithms. GECCO (Companion) 2009: 2753-2774 - [e1]Lihong Xu, Erik D. Goodman, Guoliang Chen, L. Darrell Whitley, Yongsheng Ding:
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC Summit 2009, Shanghai, China, June 12-14, 2009. ACM 2009, ISBN 978-1-60558-326-6 [contents] - 2008
- [j15]Jianjun Hu, Erik D. Goodman, Shaobo Li, Ronald C. Rosenberg:
Automated synthesis of mechanical vibration absorbers using genetic programming. Artif. Intell. Eng. Des. Anal. Manuf. 22(3): 207-217 (2008) - [j14]Jiachuan Wang, Zhun Fan, Janis P. Terpenny, Erik D. Goodman:
Cooperative body-brain coevolutionary synthesis of mechatronic systems. Artif. Intell. Eng. Des. Anal. Manuf. 22(3): 219-234 (2008) - [j13]Zhun Fan, Jiachuan Wang, Sofiane Achiche, Erik D. Goodman, Ronald C. Rosenberg:
Structured synthesis of MEMS using evolutionary approaches. Appl. Soft Comput. 8(1): 579-589 (2008) - [c43]Zhenhua Li, Erik D. Goodman:
A practical search index and population size analysis based on the building block hypothesis. GECCO 2008: 1123-1124 - [c42]Erik D. Goodman:
Introduction to genetic algorithms. GECCO (Companion) 2008: 2277-2298 - [c41]Zhenhua Li, Erik D. Goodman:
Exploring Building Blocks through Crossover. ISICA 2008: 707-714 - [p4]Erik D. Goodman, Ronald C. Averill, Ranny Sidhu:
Multi-Level Decomposition for Tractability in Structural Design Optimization. Evolutionary Computation in Practice 2008: 41-62 - 2007
- [j12]Hiram A. Firpi, Erik D. Goodman, Javier R. Echauz:
Epileptic Seizure Detection Using Genetically Programmed Artificial Features. IEEE Trans. Biomed. Eng. 54(2): 212-224 (2007) - [c40]Lihong Xu, Qingsong Hu, Erik D. Goodman:
Two layer iterative multi-objective compatible control algorithm. CDC 2007: 2992-2997 - [c39]Lihong Xu, Qingsong Hu, Erik D. Goodman:
A compatible energy-saving control algorithm for a class of conflicted multi-objective control problem. IEEE Congress on Evolutionary Computation 2007: 4446-4453 - [c38]Zhenhua Li, Erik D. Goodman:
Learning building block structure from crossover failure. GECCO 2007: 1280-1287 - [c37]Sofiane Achiche, Wei Wang, Zhun Fan, Ali Gürcan Özkil, Torben Sørensen, Jiachuan Wang, Erik D. Goodman:
Genetically generated double-level fuzzy controller with a fuzzy adjustment strategy. GECCO 2007: 1880-1887 - [c36]Erik D. Goodman:
Introduction to genetic algorithms. GECCO (Companion) 2007: 3205-3224 - [c35]Daniel Baker, Erik D. Goodman, Patrick Kane, Michael A. Shanblatt:
A Paradigm of Government/Industry/University Cooperation: A PSoC Controller for a NASA Robotic Arm. MSE 2007: 129-130 - [p3]Jianjun Hu, Shaobo Li, Erik D. Goodman:
Evolutionary Robust Design of Analog Filters Using Genetic Programming. Evolutionary Computation in Dynamic and Uncertain Environments 2007: 479-496 - [p2]Zhun Fan, Jiachuan Wang, Min Wen, Erik D. Goodman, Ronald C. Rosenberg:
An Evolutionary Approach For Robust Layout Synthesis of MEMS. Evolutionary Computation in Dynamic and Uncertain Environments 2007: 519-542 - 2006
- [p1]Zhun Fan, Mogens Andreasen, Jiachuan Wang, Erik D. Goodman, Lars Hein:
Towards an Evolvable Engineering Design Framework for Interactive Computer Design Support of Mechatronic Systems. Integrated Intelligent Systems for Engineering Design 2006: 182-198 - 2005
- [j11]Jianjun Hu, Erik D. Goodman, Kisung Seo, Zhun Fan, Rondal Rosenberg:
The Hierarchical Fair Competition (HFC) Framework for Sustainable Evolutionary Algorithms. Evol. Comput. 13(2): 241-277 (2005) - [j10]Jiachuan Wang, Zhun Fan, Janis P. Terpenny, Erik D. Goodman:
Knowledge interaction with genetic programming in mechatronic systems design using bond graphs. IEEE Trans. Syst. Man Cybern. Part C 35(2): 172-182 (2005) - [c34]Hiram A. Firpi, Erik D. Goodman, Javier R. Echauz:
On Prediction of Epileptic Seizures by Computing Multiple Genetic Programming Artificial Features. EuroGP 2005: 321-330 - [c33]Hiram A. Firpi, Erik D. Goodman, Javier R. Echauz:
Epileptic seizure detection by means of genetically programmed artificial features. GECCO 2005: 461-466 - [c32]Jianjun Hu, Xiwei Zhong, Erik D. Goodman:
Open-ended robust design of analog filters using genetic programming. GECCO 2005: 1619-1626 - [c31]Kisung Seo, Erik D. Goodman, Ronald C. Rosenberg:
Design of air pump system using bond graph and genetic programming method. GECCO 2005: 2215-2216 - 2004
- [j9]Erik D. Goodman:
A Word from the Chair of ISGEC. Genet. Program. Evolvable Mach. 5(1): 9 (2004) - [c30]Hiram A. Firpi, Erik D. Goodman:
Swarmed Feature Selection. AIPR 2004: 112-118 - [c29]Hiram A. Firpi, Erik D. Goodman:
Designing Templates for Cellular Neural Networks Using Particle Swarm Optimization. AIPR 2004: 119-123 - [c28]Jianjun Hu, Erik D. Goodman, Ronald C. Rosenberg:
Topological search in automated mechatronic system synthesis using bond graphs and genetic programming. ACC 2004: 5628-5634 - [c27]Jianjun Hu, Erik D. Goodman:
Wireless access point configuration by genetic programming. IEEE Congress on Evolutionary Computation 2004: 1178-1184 - [c26]Zhun Fan, Erik D. Goodman, Jiachuan Wang, Ronald C. Rosenberg, Kisung Seo, Jianjun Hu:
Hierarchical evolutionary synthesis of MEMS. IEEE Congress on Evolutionary Computation 2004: 2320-2327 - [c25]Kisung Seo, Jianjun Hu, Zhun Fan, Erik D. Goodman, Ronald C. Rosenberg:
Hierarchical Breeding Control for Efficient Topology/Parameter Evolution. GECCO (2) 2004: 722-723 - [c24]Bulent Buyukbozkirli, Erik D. Goodman:
A Statistical Model of GA Dynamics for the OneMax Problem. GECCO (1) 2004: 935-946 - [c23]Jianjun Hu, Erik D. Goodman:
Robust and Efficient Genetic Algorithms with Hierarchical Niching and a Sustainable Evolutionary Computation Model. GECCO (1) 2004: 1220-1232 - 2003
- [c22]Jianjun Hu, Kisung Seo, Zhun Fan, Ronald C. Rosenberg, Erik D. Goodman:
HEMO: A Sustainable Multi-objective Evolutionary Optimization Framework. GECCO 2003: 1029-1040 - [c21]Kisung Seo, Zhun Fan, Jianjun Hu, Erik D. Goodman, Ronald C. Rosenberg:
Dense and Switched Modular Primitives for Bond Graph Model Design. GECCO 2003: 1764-1775 - [c20]Zhun Fan, Kisung Seo, Jianjun Hu, Ronald C. Rosenberg, Erik D. Goodman:
System-Level Synthesis of MEMS via Genetic Programming and Bond Graphs. GECCO 2003: 2058-2071 - [c19]Zhijian Huang, Min Pei, Erik D. Goodman, Yong Huang, Gaoping Li:
Genetic Algorithm Optimized Feature Transformation - A Comparison with Different Classifiers. GECCO 2003: 2121-2133 - 2002
- [j8]Kisung Seo, Jianjun Hu, Zhun Fan, Erik D. Goodman, Ronald C. Rosenberg:
Automated design approaches for multi-domain dynamic systems using bond graphs and genetic programming. Int. J. Comput. Syst. Signals 3(1): 55-70 (2002) - [c18]Jianjun Hu, Erik D. Goodman:
The hierarchical fair competition (HFC) model for parallel evolutionary algorithms. IEEE Congress on Evolutionary Computation 2002: 49-54 - [c17]Jianjun Hu, Erik D. Goodman, Kisung Seo, Min Pei:
Adaptive Hierarchical Fair Competition (AHFC) Model For Parallel Evolutionary Algorithms. GECCO 2002: 772-779 - [c16]Jianjun Hu, Kisung Seo, Shaobo Li, Zhun Fan, Ronald C. Rosenberg, Erik D. Goodman:
Structure Fitness Sharing (SFS) For Evolutionary Design By Genetic Programming. GECCO 2002: 780-787 - [c15]Zhun Fan, Kisung Seo, Ronald C. Rosenberg, Jianjun Hu, Erik D. Goodman:
Exploring Multiple Design Topologies Using Genetic Programming And Bond Graphs. GECCO 2002: 1073-1080 - 2001
- [c14]Charles Steinfield, Marleen Huysman, Kenneth David, Chyng-Yang Jang, Jan Poot, Mirjam Huis in 't Veld, Ingrid Mulder, Erik D. Goodman, John Lloyd, Timothy Hinds, J. H. Erik Andriessen, Kirsten Jarvis, Klaas van der Werff, Angel Cabrera:
New Methods for Studying Global Virtual Teams: Towards a Multi-Faceted Approach. HICSS 2001 - 2000
- [j7]Michael L. Raymer, William F. Punch III, Erik D. Goodman, Leslie A. Kuhn, Anil K. Jain:
Dimensionality reduction using genetic algorithms. IEEE Trans. Evol. Comput. 4(2): 164-171 (2000)
1990 – 1999
- 1999
- [j6]David Eby, Ronald C. Averill, William F. Punch III, Erik D. Goodman:
Optimal design of flywheels using an injection island genetic algorithm. Artif. Intell. Eng. Des. Anal. Manuf. 13(5): 327-340 (1999) - [c13]Arnold L. Patton, Erik D. Goodman, William F. Punch III:
Scheduling variance loss using population level annealing for evolutionary computation. CEC 1999: 760-767 - 1998
- [j5]A. A. Ligun, A. A. Shumeiko, Stephen P. Radzevich, Erik D. Goodman:
Asymptotically optimum recovery of smooth contours by Bézier curve. Comput. Aided Geom. Des. 15(5): 495-506 (1998) - [c12]Arnold L. Patton, Terrence Dexter, Erik D. Goodman, William F. Punch III:
On the Application of Cohort-Driven Operators to Continuous Optimization Problems Using Evolutionary Computation. Evolutionary Programming 1998: 671-681 - [c11]Stepan P. Radzevich, Erik D. Goodman:
Efficiency of Multi-Axis NC Machining of Sculpted Part Surfaces. SSM 1998: 42-58 - 1997
- [j4]A. A. Ligun, A. A. Shumeiko, S. P. Radzevitch, Erik D. Goodman:
Asymptotically optimal disposition of tangent points for approximation of smooth convex surfaces by polygonal functions. Comput. Aided Geom. Des. 14(6): 533-546 (1997) - [c10]Shyh-Chang Lin, Erik D. Goodman, William F. Punch III:
Investigating Parallel Genetic Algorithms on Job Shop Scheduling Problems. Evolutionary Programming 1997: 383-393 - [c9]Shyh-Chang Lin, Erik D. Goodman, William F. Punch III:
A Genetic Algorithm Approach to Dynamic Job Shop Scheduling Problem. ICGA 1997: 481-488 - [c8]Michael L. Raymer, William F. Punch III, Erik D. Goodman, Paul C. Sanschagrin, Leslie A. Kuhn:
Simultanous Feature Extraction and Selection Using a Genetic Algorithm. ICGA 1997: 561-567 - [c7]Gang Wang, Erik D. Goodman, William F. Punch III:
Toward the Optimization of a Class of Black Box Optimization Algorithms. ICTAI 1997: 348-356 - 1995
- [j3]William F. Punch III, Ronald C. Averill, Erik D. Goodman, Shyh-Chang Lin, Ying Ding:
Using Genetic Algorithms to Design Laminated Composite Structures. IEEE Expert 10(1): 42-49 (1995) - [c6]Arnold L. Patton, William F. Punch III, Erik D. Goodman:
A Standard GA Approach to Native Protein Conformation Prediction. ICGA 1995: 574-581 - 1994
- [c5]Shyh-Chang Lin, William F. Punch III, Erik D. Goodman:
Coarse-grain parallel genetic algorithms: categorization and new approach. SPDP 1994: 28-37 - 1993
- [c4]William F. Punch III, Erik D. Goodman, Min Pei, Lai Chia-Shun, Paul D. Hovland, Richard J. Enbody:
Further Research on Feature Selection and Classification Using Genetic Algorithms. ICGA 1993: 557-564 - 1991
- [c3]Erik D. Goodman, Leslie T. W. Hoppensteradt:
A method for accurate simulation of robotic spray application using empirical parameterization. ICRA 1991: 1357-1368 - 1990
- [j2]James H. Oliver, Erik D. Goodman:
Direct dimensional NC verification. Comput. Aided Des. 22(1): 3-9 (1990)
1980 – 1989
- 1988
- [c2]Adrian V. Sannier II, Erik D. Goodman:
Midgard: A Genetic Approach to Adaptive Load Balancing for Distributed Systems. ML 1988: 174-180 - 1987
- [c1]Adrian V. Sannier II, Erik D. Goodman:
Genetic Learning Procedures in Distributed Environments. ICGA 1987: 162-169
1970 – 1979
- 1970
- [j1]Erik D. Goodman:
R70-18 Real-Time Computation by n-Dimensional Iterative Arrays of Finite-State Machines. IEEE Trans. Computers 19(7): 657-658 (1970)
Coauthor Index
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