Search Results - "Evolutionary multi-objective algorithms"

Fair Performance Comparison of Evolutionary Multi-Objective Algorithms

Authors: Hisao Ishibuchi Lie Meng Pang

Source: Proceedings of the Genetic and Evolutionary Computation Conference Companion. :1125-1152

Why Dominance Is Not Enough: Lessons from Practical Evolutionary Multi-Objective Algorithms

Authors: Duc-Cuong Dang Andre Opris Dirk Sudholt

Source: Proceedings of the Genetic and Evolutionary Computation Conference. :1604-1612

Integrating Active Learning for Improved Preference Modeling in Tree-Based Interactive Evolutionary Multi-Objective Algorithms

Authors: Seyed Mahdi Shavarani Mahmoud Golabi Lhassane Idoumghar

Source: 2025 IEEE Congress on Evolutionary Computation (CEC). :1-8

Runtime Analysis of Functions Where Widely-Used Evolutionary Multi-Objective Algorithms Beat Simple Ones

Authors: Duc-Cuong Dang Andre Opris Dirk Sudholt

Source: ACM Transactions on Evolutionary Learning and Optimization.

Exploring Long-term Memory in Evolutionary Multi-objective Algorithms: A Case Study with NSGA-III

Authors: Masoud Kermani Poor Shahryar Rahnamayan Azam Asilian Bidgoli et al.

Source: 2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). :864-870

Illustrating the Efficiency of Popular Evolutionary Multi-Objective Algorithms Using Runtime Analysis

Authors: Duc-Cuong Dang Andre Opris Dirk Sudholt

Source: Proceedings of the Genetic and Evolutionary Computation Conference. :484-492

Subject Terms: FOS: Computer and information sciences, F.2.0, I.2.8, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE)

Access URL: http://arxiv.org/abs/2405.13572

Interactive tool for visualizing the comprehensive performance of evolutionary multi-objective algorithms applied to problems with two or three objectives

Authors: Michał Tomczyk Miłosz Kadziński

Source: Proceedings of the Genetic and Evolutionary Computation Conference Companion. :375-378

Performance Evaluation of Evolutionary Multi-Objective Algorithms Using Real-World Problems with an Additional Total Constraint Violation Objective

Authors: Yang Nan Hisao Ishibuchi Tianye Shu

Source: 2024 IEEE Congress on Evolutionary Computation (CEC). :1-6

Analysis of evolutionary multi-objective algorithms for data center electrical systems

Authors: Francisco Monte Sousa Gustavo Callou

Source: Computing. 107

Tutorial Series on Java Framework for Evolutionary Computation and Decision Making. Tutorial 6: Visualizing the comprehensive performance of evolutionary multi-objective algorithms applied to problems with two or three objectives (IVEMO: Heatmap)

Authors: Tomczyk, Michał

Subject Terms: JECDM, Interactive visualization tools

Reliability of Indicator-Based Comparison Results of Evolutionary Multi-objective Algorithms

Authors: Lie Meng Pang Hisao Ishibuchi Yang Nan et al.

Source: Lecture Notes in Computer Science ISBN: 9783031700842

Illustrating the Efficiency of Popular Evolutionary Multi-Objective Algorithms Using Runtime Analysis

Authors: Dang, Duc-Cuong Opris, Andre Sudholt, Dirk

Index Terms: Computer Science - Neural and Evolutionary Computing, F.2.0, I.2.8, text

URL: http://arxiv.org/abs/2405.13572

Evolutionary multi-objective algorithms for feed resource allocation in dairy systems

Authors: Gaston Notte Pablo Chilibroste Martin Pedemonte et al.

Source: 2021 IEEE Latin American Conference on Computational Intelligence (LA-CCI). :1-6

Optimising Monotone Chance-Constrained Submodular Functions Using Evolutionary Multi-objective Algorithms

Authors: Aneta Neumann Frank Neumann

Source: Lecture Notes in Computer Science ISBN: 9783030581114

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, Computer Science - Neural and Evolutionary Computing, 0102 computer and information sciences, 02 engineering and technology, Neural and Evolutionary Computing (cs.NE), 01 natural sciences, Machine Learning (cs.LG)

Access URL: http://arxiv.org/pdf/2006.11444
https://pubmed.ncbi.nlm.nih.gov/39316732
http://arxiv.org/abs/2006.11444
https://rd.springer.com/chapter/10.1007/978-3-030-58112-1_28
https://arxiv.org/pdf/2006.11444
https://link.springer.com/chapter/10.1007/978-3-030-58112-1_28
https://dblp.uni-trier.de/db/conf/ppsn/ppsn2020-1.html#NeumannN20
https://arxiv.org/abs/2006.11444

On Benchmarking Interactive Evolutionary Multi-Objective Algorithms: Supplementary Material

Authors: Shavarani, Seyed Mahdi López-Ibáñez, Manuel Knowles, Joshua

Subject Terms: Benchmarking, Interactive Optimization, Multi-Objective Optimization, Multicriteria Decision-Making, Machine Decision-Makers

A comparative study on evolutionary multi-objective algorithms for next release problem

Authors: Rahimi, I Gandomi, AH Nikoo, MR et al.

Index Terms: 0102 Applied Mathematics, 0801 Artificial Intelligence and Image Processing, 0806 Information Systems, Journal Article

URL: http://hdl.handle.net/10453/175922
Applied Soft Computing
10.1016/j.asoc.2023.110472

Evolutionary Multi-Objective Algorithms for the Knapsack Problems with Stochastic Profits

Authors: Perera, Kokila Neumann, Aneta Neumann, Frank

Index Terms: Computer Science - Neural and Evolutionary Computing, text

URL: http://arxiv.org/abs/2303.01695

Towards Self-adaptive Mutation in Evolutionary Multi-Objective Algorithms

Authors: Ye, Furong Neumann, Frank de Nobel, Jacob et al.

Subject Terms: FOS: Computer and information sciences, 0202 electrical engineering, electronic engineering, information engineering, Computer Science - Neural and Evolutionary Computing, 0102 computer and information sciences, 02 engineering and technology, Neural and Evolutionary Computing (cs.NE), 01 natural sciences

Access URL: http://arxiv.org/abs/2303.04611

Optimizing Monotone Chance-Constrained Submodular Functions Using Evolutionary Multi-Objective Algorithms

Authors: Neumann, Aneta Neumann, Frank

Index Terms: Computer Science - Neural and Evolutionary Computing, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2006.11444

A Comparative Study on Evolutionary Multi-objective Algorithms for Next Release Problem

Authors: Rahimi, I Gandomi, AH Nikoo, MR et al.

Index Terms: Preprint

URL: http://hdl.handle.net/10453/169147
Research Square
10.21203/rs.3.rs-1929133/v1