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ORCID12th EMO 2023: Leiden, The Netherlands
- Michael Emmerich
, André H. Deutz, Hao Wang, Anna V. Kononova, Boris Naujoks, Ke Li, Kaisa Miettinen, Iryna Yevseyeva:
Evolutionary Multi-Criterion Optimization - 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20-24, 2023, Proceedings. Lecture Notes in Computer Science 13970, Springer 2023, ISBN 978-3-031-27249-3
Algorithm Design and Engineering
- Tea Tusar, Aljosa Vodopija, Bogdan Filipic:
Visual Exploration of the Effect of Constraint Handling in Multiobjective Optimization. 3-16 - Fei Liu, Qingfu Zhang:
A Two-Stage Algorithm for Integer Multiobjective Simulation Optimization. 17-28 - Ritam Guha, Kalyanmoy Deb:
RegEMO: Sacrificing Pareto-Optimality for Regularity in Multi-objective Problem-Solving. 29-42 - Rui Zhong, Masaharu Munetomo:
Cooperative Coevolutionary NSGA-II with Linkage Measurement Minimization for Large-Scale Multi-objective Optimization. 43-55 - Renzhi Chen, Ke Li:
Data-Driven Evolutionary Multi-objective Optimization Based on Multiple-Gradient Descent for Disconnected Pareto Fronts. 56-70 - Balija Santoshkumar, Kalyanmoy Deb, Lei Chen:
Eliminating Non-dominated Sorting from NSGA-III. 71-85 - António Gaspar-Cunha, Paulo Costa, Francisco José Monaco, Alexandre C. B. Delbem:
Scalability of Multi-objective Evolutionary Algorithms for Solving Real-World Complex Optimization Problems. 86-100
Machine Learning and Multi-criterion Optimization
- Timo M. Deist, Monika Grewal, Frank J. W. M. Dankers, Tanja Alderliesten, Peter A. N. Bosman:
Multi-objective Learning Using HV Maximization. 103-117 - Phoenix Neale Williams, Ke Li, Geyong Min:
Sparse Adversarial Attack via Bi-objective Optimization. 118-133 - Drishti Bhasin, Sajag Swami, Sarthak Sharma, Saumya Sah, Dhish Kumar Saxena, Kalyanmoy Deb:
Investigating Innovized Progress Operators with Different Machine Learning Methods. 134-146 - Shiqing Liu, Xueming Yan, Yaochu Jin:
End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location. 147-161 - Julia Heise, Sanaz Mostaghim:
Online Learning Hyper-Heuristics in Multi-Objective Evolutionary Algorithms. 162-175 - Kaifeng Yang, Michael Affenzeller:
Surrogate-assisted Multi-objective Optimization via Genetic Programming Based Symbolic Regression. 176-190 - Kalyanmoy Deb, Aryan Gondkar, Anirudh Suresh:
Learning to Predict Pareto-Optimal Solutions from Pseudo-weights. 191-204 - Hao Hao, Aimin Zhou:
A Relation Surrogate Model for Expensive Multiobjective Continuous and Combinatorial Optimization. 205-217 - Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling. 218-230 - Jinyuan Zhang, Linjun He, Hisao Ishibuchi:
An Improved Fuzzy Classifier-Based Evolutionary Algorithm for Expensive Multiobjective Optimization Problems with Complicated Pareto Sets. 231-246 - Ping Guo, Qingfu Zhang, Xi Lin:
Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables. 247-259 - Arnaud Liefooghe, Sébastien Vérel, Tinkle Chugh, Jonathan E. Fieldsend, Richard Allmendinger, Kaisa Miettinen:
Feature-Based Benchmarking of Distance-Based Multi/Many-objective Optimisation Problems: A Machine Learning Perspective. 260-273
Benchmarking and Performance Assessment
- Lie Meng Pang, Yang Nan, Hisao Ishibuchi:
Partially Degenerate Multi-objective Test Problems. 277-290 - Lennart Schäpermeier, Pascal Kerschke, Christian Grimme, Heike Trautmann:
Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets. 291-304 - Sebastian Mai, Tobias Benecke, Sanaz Mostaghim:
MACO: A Real-World Inspired Benchmark for Multi-objective Evolutionary Algorithms. 305-318 - Victoria Johnson, João A. Duro, Visakan Kadirkamanathan, Robin C. Purshouse:
A Scalable Test Suite for Bi-objective Multidisciplinary Optimization. 319-332 - Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Performance Evaluation of Multi-objective Evolutionary Algorithms Using Artificial and Real-world Problems. 333-347 - Diana Cristina Valencia-Rodríguez, Carlos A. Coello Coello:
A Novel Performance Indicator Based on the Linear Assignment Problem. 348-360 - Angus Kenny, Tapabrata Ray, Hemant Kumar Singh, Xiaodong Li:
A Test Suite for Multi-objective Multi-fidelity Optimization. 361-373
Indicator Design and Complexity Analysis
- Steve Huntsman:
Diversity Enhancement via Magnitude. 377-390 - Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems. 391-404 - André H. Deutz, Michael Emmerich, Hao Wang:
The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. 405-418 - Ved Prakash, Sumit Mishra, Carlos A. Coello Coello:
On the Computational Complexity of Efficient Non-dominated Sort Using Binary Search. 419-432
Applications in Real World Domains
- Krzysztof Michalak:
Evolutionary Algorithms with Machine Learning Models for Multiobjective Optimization in Epidemics Control. 435-448 - Sagnik Sarkar, Siddhartha Devapujula, Hrishikesh Vidyadhar Ganu, Chaithanya Bandi, Ravindra Babu Tallamraju, Chilamakurthi Vamsikrishna Satya, Siddhant Doshi:
Joint Price Optimization Across a Portfolio of Fashion E-Commerce Products. 449-461 - Clément Legrand, Diego Cattaruzza, Laetitia Jourdan, Marie-Eléonore Kessaci:
Improving MOEA/D with Knowledge Discovery. Application to a Bi-objective Routing Problem. 462-475 - Ksenia Pereverdieva, Michael Emmerich, André H. Deutz, Tessa Ezendam, Thomas Bäck, Hèrm Hofmeyer:
The Prism-Net Search Space Representation for Multi-objective Building Spatial Design. 476-489 - Susanne Rosenthal:
Selection Strategies for a Balanced Multi- or Many-Objective Molecular Optimization and Genetic Diversity: A Comparative Study. 490-503 - Paramita Biswas, Anirban Mukhopadhyay:
A Multi-objective Evolutionary Framework for Identifying Dengue Stage-Specific Differentially Co-expressed and Functionally Enriched Gene Modules. 504-517 - Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
Real-World Airline Crew Pairing Optimization: Customized Genetic Algorithm Versus Column Generation Method. 518-531 - Krzysztof Michalak, Mario Giacobini:
Multiobjective Optimization of Evolutionary Neural Networks for Animal Trade Movements Prediction. 532-545 - André Thomaser, Marc-Eric Vogt, Anna V. Kononova, Thomas Bäck:
Transfer of Multi-objectively Tuned CMA-ES Parameters to a Vehicle Dynamics Problem. 546-560
Multi-criteria Decision Making and Interactive Algorithms
- Linjun He, Yang Nan, Hisao Ishibuchi, Dipti Srinivasan:
Preference-Based Nonlinear Normalization for Multiobjective Optimization. 563-577 - Giomara Lárraga, Bhupinder Singh Saini, Kaisa Miettinen:
Incorporating Preference Information Interactively in NSGA-III by the Adaptation of Reference Vectors. 578-592 - Bekir Afsar, Johanna M. Silvennoinen, Kaisa Miettinen:
A Systematic Way of Structuring Real-World Multiobjective Optimization Problems. 593-605 - Abhiroop Ghosh, Kalyanmoy Deb, Ronald C. Averill, Erik D. Goodman:
IK-EMOViz: An Interactive Knowledge-Based Evolutionary Multi-objective Optimization Framework. 606-619 - Seyed Mahdi Shavarani, Manuel López-Ibáñez, Richard Allmendinger, Joshua D. Knowles:
An Interactive Decision Tree-Based Evolutionary Multi-objective Algorithm. 620-634
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