Abstract:
We present four abstract evolutionary algorithms for multi-objective optimization and theoretical results that characterize their convergence behavior. Thanks to these re...Show MoreMetadata
Abstract:
We present four abstract evolutionary algorithms for multi-objective optimization and theoretical results that characterize their convergence behavior. Thanks to these results it is easy to verify whether or not a particular instantiation of these abstract evolutionary algorithms offers the desired limit behavior. Several examples are given.
Published in: Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)
Date of Conference: 16-19 July 2000
Date Added to IEEE Xplore: 06 August 2002
Print ISBN:0-7803-6375-2
Citations are not available for this document.
Cites in Papers - |
Cites in Papers - IEEE (38)
Select All
1.
Chenguang Yang, Lei Zhao, Zhige Xie, Aizhi Liu, "Convergence Analysis and a Multi-Objective Optimization Algorithm for Bee Colonies Utilizing the Nelder-Mead Method", 2024 International Conference on Advances in Electrical Engineering and Computer Applications (AEECA), pp.428-435, 2024.
2.
Miqing Li, Manuel López-Ibáñez, Xin Yao, "Multi-Objective Archiving", IEEE Transactions on Evolutionary Computation, vol.28, no.3, pp.696-717, 2024.
3.
Zabia Djallal Eddine, Kraa Okba, Afghoul Hamza, "Grey wolf optimization parameter enhancement for tracking the maximum power point of PV system under multiple cluster complex partial shading", 2022 19th International Multi-Conference on Systems, Signals & Devices (SSD), pp.2004-2009, 2022.
4.
Cunli Song, "A Hybrid Multi-Objective Teaching-Learning Based Optimization for Scheduling Problem of Hybrid Flow Shop With Unrelated Parallel Machine", IEEE Access, vol.9, pp.56822-56835, 2021.
5.
Long Zhao, Jingxuan Wei, "A New Bi-level PSO Algorithm based on Dynamic Constraint Processing and Approximate Navigation", 2019 IEEE Congress on Evolutionary Computation (CEC), pp.1659-1663, 2019.
6.
Dhish Kumar Saxena, Arnab Sinha, João A. Duro, Qingfu Zhang, "Entropy-Based Termination Criterion for Multiobjective Evolutionary Algorithms", IEEE Transactions on Evolutionary Computation, vol.20, no.4, pp.485-498, 2016.
7.
Long Nguyen, Lam Thu Bui, Hussein Abbass, "A new niching method for the direction-based multi-objective evolutionary algorithm", 2013 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM), pp.1-8, 2013.
8.
Sauli Ruuska, Kaisa Miettinen, "Constructing evolutionary algorithms for bilevel multiobjective optimization", 2012 IEEE Congress on Evolutionary Computation, pp.1-7, 2012.
9.
Alfredo Arias-Montano, Carlos A. Coello Coello, Efrén Mezura-Montes, "Multiobjective Evolutionary Algorithms in Aeronautical and Aerospace Engineering", IEEE Transactions on Evolutionary Computation, vol.16, no.5, pp.662-694, 2012.
10.
Jingxuan Wei, Mengjie Zhang, "A memetic particle swarm optimization for constrained multi-objective optimization problems", 2011 IEEE Congress of Evolutionary Computation (CEC), pp.1636-1643, 2011.
11.
Zhi-yong Li, Chao Chen, Chang-an Ren, Esraa M. Mohammed, "Novel Objective-Space-Dividing Multi-objectives evolutionary algorithm and its convergence property", 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), pp.372-379, 2010.
12.
Lily Rachmawati, Dipti Srinivasan, "Incorporating the Notion of Relative Importance of Objectives in Evolutionary Multiobjective Optimization", IEEE Transactions on Evolutionary Computation, vol.14, no.4, pp.530-546, 2010.
13.
Eckart Zitzler, Lothar Thiele, Johannes Bader, "On Set-Based Multiobjective Optimization", IEEE Transactions on Evolutionary Computation, vol.14, no.1, pp.58-79, 2010.
14.
Louis-Claude Canon, Emmanuel Jeannot, "Evaluation and Optimization of the Robustness of DAG Schedules in Heterogeneous Environments", IEEE Transactions on Parallel and Distributed Systems, vol.21, no.4, pp.532-546, 2010.
15.
Luis Marti, Jesus Garcia, Antonio Berlanga, Jose M. Molina, "An approach to stopping criteria for multi-objective optimization evolutionary algorithms: The MGBM criterion", 2009 IEEE Congress on Evolutionary Computation, pp.1263-1270, 2009.
16.
David Iclanzan, D. Dumitrescu, "How Can Artificial Neural Networks Help Making the Intractable Search Spaces Tractable", 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), pp.4015-4022, 2008.
17.
Alessandro G. Di Nuovo, Vincenzo Catania, "An evolutionary fuzzy c-means approach for clustering of bio-informatics databases", 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), pp.2077-2082, 2008.
18.
Zhuo Kang, Lishan Kang, Changhe Li, Yuping Chen, Minzhong Liu, "Convergence properties of E-optimality algorithms for Many objective Optimization Problems", 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), pp.472-477, 2008.
19.
Louis-Claude Canon, Emmanuel Jeannot, "Scheduling strategies for the bicriteria optimization of the robustness and makespan", 2008 IEEE International Symposium on Parallel and Distributed Processing, pp.1-8, 2008.
20.
Thomas Hanne, "A primal-dual multiobjective evolutionary algorithm for approximating the efficient set", 2007 IEEE Congress on Evolutionary Computation, pp.3127-3134, 2007.
21.
L. Rachmawati, D. Srinivasan, "Dynamic resizing for grid-based archiving in evolutionary multi objective optimization", 2007 IEEE Congress on Evolutionary Computation, pp.3975-3982, 2007.
22.
C. K. Goh, K. C. Tan, "An Investigation on Noisy Environments in Evolutionary Multiobjective Optimization", IEEE Transactions on Evolutionary Computation, vol.11, no.3, pp.354-381, 2007.
23.
Martin Brown, Nicky Hutauruk, "On the Convergence of Multi-Objective Descent Algorithms", 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, pp.253-260, 2007.
24.
Xinling Zhou, Chengyi Sun, X. Z. Gao, "Scored Pareto MEC for Multi-Objective Optimization and Its Convergence", 2006 IEEE International Conference on Systems, Man and Cybernetics, vol.2, pp.1580-1586, 2006.
25.
C. K. Goh, S. C. Chiam, K. C. Tan, "An Investigation on Noisy Environments in Evolutionary Multi-Objective Optimization", 2006 IEEE Conference on Cybernetics and Intelligent Systems, pp.1-7, 2006.
26.
C.A. Coello Coello, "Evolutionary multi-objective optimization: a historical view of the field", IEEE Computational Intelligence Magazine, vol.1, no.1, pp.28-36, 2006.
27.
F. Xue, A.C. Sanderson, R.J. Graves, "Multi-objective differential evolution - algorithm, convergence analysis, and applications", 2005 IEEE Congress on Evolutionary Computation, vol.1, pp.743-750 Vol.1, 2005.
28.
M. Laumanns, L. Thiele, E. Zitzler, "Running time analysis of multiobjective evolutionary algorithms on pseudo-Boolean functions", IEEE Transactions on Evolutionary Computation, vol.8, no.2, pp.170-182, 2004.
29.
O. Giel, "Expected runtimes of a simple multi-objective evolutionary algorithm", The 2003 Congress on Evolutionary Computation, 2003. CEC '03., vol.3, pp.1918-1925 Vol.3, 2003.
30.
Zhijian Wu, Lishan Kang, "A fast and elitist parallel evolutionary algorithm for solving systems of non-linear equations", The 2003 Congress on Evolutionary Computation, 2003. CEC '03., vol.2, pp.1026-1028 Vol.2, 2003.
Cites in Papers - Other Publishers (58)
1.
Carlos A. Coello Coello, "Recent Research Topics in Evolutionary Multiobjective Optimization: A Personal Perspective", Computational Intelligence, vol.1119, pp.90, 2023.
2.
Dhruv Khandelwal, Maarten Schoukens, Roland Toth, "Automated multi-objective system identification using grammar-based genetic programming", Automatica, vol.154, pp.111017, 2023.
3.
Haoxiang Xue, Massimiliano Gobbi, Andrea Matta, "Multi-fidelity surrogate-based optimal design of road vehicle suspension systems", Optimization and Engineering, 2023.
4.
Dhruv Khandelwal, "Evolutionary Multi-criteria System Identification", Automating Data-Driven Modelling of Dynamical Systems, pp.125, 2022.
5.
Arvinder Kaur, Yugal Kumar, "A multi-objective vibrating particle system algorithm for data clustering", Pattern Analysis and Applications, vol.25, no.1, pp.209, 2022.
6.
J. Rajalakshmi, S. Durairaj, "Application of multi-objective optimization algorithm for siting and sizing of distributed generations in distribution networks", Journal of Combinatorial Optimization, vol.41, no.2, pp.267, 2021.
7.
M. Cunha, J. Marques, "A New Multiobjective Simulated Annealing Algorithm?MOSA?GR: Application to the Optimal Design of Water Distribution Networks", Water Resources Research, vol.56, no.3, 2020.
8.
Carlos A. Coello Coello, Silvia Gonzalez Brambila, Josue Figueroa Gamboa, Ma Guadalupe Castillo Tapia, Raquel Hernandez Gomez, "Evolutionary multiobjective optimization: open research areas and some challenges lying ahead", Complex & Intelligent Systems, vol.6, no.2, pp.221, 2020.
9.
Long Zhao, JingXuan Wei, "A nested particle swarm algorithm based on sphere mutation to solve bi-level optimization", Soft Computing, vol.23, no.21, pp.11331, 2019.
10.
Miqing Li, Xin Yao, "An Empirical Investigation of the Optimality and Monotonicity Properties of Multiobjective Archiving Methods", Evolutionary Multi-Criterion Optimization, vol.11411, pp.15, 2019.
11.
Carlos A. Coello Coello, Handbook of Heuristics, pp.177, 2018.
12.
O. Schutze, C. Hernandez, E-G. Talbi, J. Q. Sun, Y. Naranjani, F.-R. Xiong, "Archivers for the representation of the set of approximate solutions for MOPs", Journal of Heuristics, 2018.
13.
Michael T. M. Emmerich, Andre H. Deutz, "A tutorial on multiobjective optimization: fundamentals and evolutionary methods", Natural Computing, 2018.
14.
Carlos A. Coello Coello, Handbook of Heuristics, pp.1, 2018.
15.
Carlos A. Coello Coello, Theory and Practice of Natural Computing, vol.10687, pp.3, 2017.
16.
El-Desouky Rahmo, Marcin Studniarski, "Generating Epsilon-Efficient Solutions in Multiobjective Optimization by Genetic Algorithm", Applied Mathematics, vol.08, no.03, pp.395, 2017.
17.
Metaheuristics for Big Data, pp.161, 2016.
18.
Rommel G. Regis, "On the Convergence of Adaptive Stochastic Search Methods for Constrained and Multi-objective Black-Box Optimization", Journal of Optimization Theory and Applications, 2016.
19.
Shahin Rostami, Alex Shenfield, "A multi-tier adaptive grid algorithm for the evolutionary multi-objective optimisation of complex problems", Soft Computing, 2016.
20.
Christoph Meier, Ali A. Yassine, Tyson R. Browning, Ulrich Walter, "Optimizing time?cost trade-offs in product development projects with a multi-objective evolutionary algorithm", Research in Engineering Design, 2016.
21.
Kalyanmoy Deb, Kalyanmoy Deb, "Multi-objective Optimization", Search Methodologies, pp.403, 2014.
22.
José L. Guerrero, Antonio Berlanga, José M. Molina, "A Guided Mutation Operator for Dynamic Diversity Enhancement in Evolutionary Strategies", International Journal of Natural Computing Research, vol.4, no.2, pp.20, 2014.
23.
P.M. Reed, D. Hadka, J.D. Herman, J.R. Kasprzyk, J.B. Kollat, "Evolutionary multiobjective optimization in water resources: The past, present, and future", Advances in Water Resources, vol.51, pp.438, 2013.
24.
D. DAmbrosio, W. Spataro, R. Rongo, G.G.R. Iovine, Treatise on Geomorphology, pp.74, 2013.
25.
David Hadka, Patrick Reed, "Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework", Evolutionary Computation, vol.21, no.2, pp.231-259, 2013.
26.
Bing Du, Huaping Chen, George Q. Huang, H. D. Yang, Multi-objective Evolutionary Optimisation for Product Design and Manufacturing, pp.279, 2011.
27.
Marcin Studniarski, "Finding all minimal elements of a finite partially ordered set by genetic algorithm with a prescribed probability", Numerical Algebra, Control and Optimization, vol.1, no.3, pp.389, 2011.
28.
Lam T. Bui, Jing Liu, Axel Bender, Michael Barlow, Slawomir Wesolkowski, Hussein A. Abbass, "DMEA: a direction-based multiobjective evolutionary algorithm", Memetic Computing, vol.3, no.4, pp.271, 2011.
29.
Oliver Schutze, Massimiliano Vasile, Carlos A. Coello Coello, "Computing the Set of Epsilon-Efficient Solutions in Multiobjective Space Mission Design", Journal of Aerospace Computing, Information, and Communication, vol.8, no.3, pp.53, 2011.
30.
Tushar Goel, Nielen Stander, "A Study of the Convergence Characteristics of Multiobjective Evolutionary Algorithms", 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference, 2010.