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Evolutionary Multi-Criterion Optimization 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20–24, 2023, Proceedings /

This book constitutes the refereed proceedings of the 12th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2022 held in Leiden, The Netherlands, during March 20-24, 2023. The 44 regular papers presented in this book were carefully reviewed and selected from 65 submissions....

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Bibliographische Detailangaben
Körperschaft: SpringerLink (Online service)
Weitere Verfasser: Emmerich, Michael (HerausgeberIn), Deutz, André (HerausgeberIn), Wang, Hao (HerausgeberIn), Kononova, Anna V. (HerausgeberIn), Naujoks, Boris (HerausgeberIn), Li, Ke (HerausgeberIn), Miettinen, Kaisa (HerausgeberIn), Yevseyeva, Iryna (HerausgeberIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Ausgabe:1st ed. 2023.
Schriftenreihe:Lecture Notes in Computer Science, 13970
Schlagworte:
Algorithms.
Computer science > Mathematics.
Artificial intelligence.
Computers.
Computer networks .
Social sciences > Data processing.
Design and Analysis of Algorithms.
Mathematics of Computing.
Artificial Intelligence.
Computing Milieux.
Computer Communication Networks.
Computer Application in Social and Behavioral Sciences.
Online-Zugang:https://doi.org/10.1007/978-3-031-27250-9
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Inhaltsangabe:
  • Algorithm Design and Engineering
  • Visual Exploration of the Effect of Constraint Handling in Multiobjective Optimization
  • A Two-stage Algorithm for Integer Multiobjective Simulation Optimization
  • RegEMO: Sacrificing Pareto-Optimality for Regularity in Multi-objective Problem-Solving
  • Cooperative coevolutionary NSGA-II with Linkage Measurement Minimization for Large-scale Multi-objective Optimization
  • Data-Driven Evolutionary Multi-Objective Optimization Based on Multiple-Gradient Descent for Disconnected Pareto Fronts
  • Eliminating Non-dominated Sorting from NSGA-III
  • Scalability of Multi-Objective Evolutionary Algorithms for Solving Real-World Complex Optimization Problems
  • Machine Learning and Multi-criterion Optimization
  • Multi-Objective Learning using HV Maximization
  • Sparse Adversarial Attack via Bi-Objective Optimization
  • Investigating Innovized Progress Operators with Different Machine Learning Methods
  • End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location
  • Online Learning Hyper-Heuristics in Multi-Objective Evolutionary Algorithms
  • Surrogate-assisted Multi-objective Optimization via Genetic Programming based Symbolic Regression
  • Learning to Predict Pareto-optimal Solutions From Pseudo-weights
  • A Relation Surrogate Model for Expensive Multiobjective Continuous and Combinatorial Optimization
  • Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling
  • Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling
  • Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables
  • Feature-based Benchmarking of Distance-based Multi/Many-objective Optimisation Problems: A Machine Learning Perspective
  • Benchmarking and Performance Assessment
  • Partially Degenerate Multi-Objective Test Problems
  • Peak-A-Boo! GeneratingMulti-Objective Multiple Peaks Benchmark Problems with Precise Pareto Sets
  • MACO: A Real-world inspired Benchmark for Multi-objective Evolutionary Algorithms
  • A scalable test suite for bi-objective multidisciplinary optimisation
  • Performance Evaluation of Multi-Objective Evolutionary Algorithms using Artificial and Real-World Problems
  • A Novel Performance Indicator based on the Linear Assignment Problem
  • A Test Suite for Multi-objective Multi-fidelity Optimization
  • Indicator Design and Complexity Analysis
  • Diversity enhancement via magnitude
  • Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems
  • Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems
  • On the Computational Complexity of Efficient Non-Dominated Sort using Binary Search
  • Applications in Real World Domains
  • Evolutionary Algorithms with Machine Learning Models for Multiobjective Optimization in Epidemics Control
  • Joint Price Optimization across a Portfolio of Fashion E-commerce Products
  • Improving MOEA/D with Knowledge Discovery. Application to a Bi-Objective Routing Problem
  • The Prism-Net Search Space Representation for Multi-Objective Building Spatial Design
  • Selection Strategies for a Balanced Multi- or Many-Objective Molecular Optimization and Genetic Diversity: a Comparative Study
  • A Multi-objective Evolutionary Framework for Identifying Dengue Stage-Specific Differentially Co-expressed and Functionally Enriched Gene Modules
  • A Multi-objective Evolutionary Framework for Identifying Dengue Stage-Specific Differentially Co-expressed and Functionally Enriched Gene Modules. -Multiobjective Optimization of Evolutionary Neural Networks for Animal Trade Movements Prediction
  • Transfer of Multi-Objectively Tuned CMA-ES Parameters to a Vehicle Dynamics Problem
  • Multi-Criteria Decision Making and Interactive Algorithms
  • Preference-Based Nonlinear Normalization for Multiobjective Optimization
  • Incorporating preference information interactively in NSGA-III by the adaptation of reference vectors
  • A Systematic Way of Structuring Real-World Multiobjective Optimization Problems
  • IK-EMOViz: An Interactive Knowledge-based Evolutionary Multi-objective Optimization Framework
  • An Interactive Decision Tree-Based Evolutionary Multi-Objective Algorithm.

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