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Evolutionary Multi-Criterion Optimization

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Cover of 'Evolutionary Multi-Criterion Optimization'

Table of Contents

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    Book Overview
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    Chapter 1 Visual Exploration of the Effect of Constraint Handling in Multiobjective Optimization
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    Chapter 2 A Two-Stage Algorithm for Integer Multiobjective Simulation Optimization
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    Chapter 3 RegEMO: Sacrificing Pareto-Optimality for Regularity in Multi-objective Problem-Solving
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    Chapter 4 Cooperative Coevolutionary NSGA-II with Linkage Measurement Minimization for Large-Scale Multi-objective Optimization
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    Chapter 5 Data-Driven Evolutionary Multi-objective Optimization Based on Multiple-Gradient Descent for Disconnected Pareto Fronts
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    Chapter 6 Eliminating Non-dominated Sorting from NSGA-III
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    Chapter 7 Scalability of Multi-objective Evolutionary Algorithms for Solving Real-World Complex Optimization Problems
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    Chapter 8 Multi-objective Learning Using HV Maximization
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    Chapter 9 Sparse Adversarial Attack via Bi-objective Optimization
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    Chapter 10 Investigating Innovized Progress Operators with Different Machine Learning Methods
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    Chapter 11 End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location
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    Chapter 12 Online Learning Hyper-Heuristics in Multi-Objective Evolutionary Algorithms
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    Chapter 13 Surrogate-assisted Multi-objective Optimization via Genetic Programming Based Symbolic Regression
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    Chapter 14 Learning to Predict Pareto-Optimal Solutions from Pseudo-weights
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    Chapter 15 A Relation Surrogate Model for Expensive Multiobjective Continuous and Combinatorial Optimization
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    Chapter 16 Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling
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    Chapter 17 An Improved Fuzzy Classifier-Based Evolutionary Algorithm for Expensive Multiobjective Optimization Problems with Complicated Pareto Sets
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    Chapter 18 Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables
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    Chapter 19 Feature-Based Benchmarking of Distance-Based Multi/Many-objective Optimisation Problems: A Machine Learning Perspective
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    Chapter 20 Partially Degenerate Multi-objective Test Problems
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    Chapter 21 Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets
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    Chapter 22 MACO: A Real-World Inspired Benchmark for Multi-objective Evolutionary Algorithms
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    Chapter 23 A Scalable Test Suite for Bi-objective Multidisciplinary Optimization
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    Chapter 24 Performance Evaluation of Multi-objective Evolutionary Algorithms Using Artificial and Real-world Problems
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    Chapter 25 A Novel Performance Indicator Based on the Linear Assignment Problem
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    Chapter 26 A Test Suite for Multi-objective Multi-fidelity Optimization
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    Chapter 27 Diversity Enhancement via Magnitude
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    Chapter 28 Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems
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    Chapter 29 The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity
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    Chapter 30 On the Computational Complexity of Efficient Non-dominated Sort Using Binary Search
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    Chapter 31 Evolutionary Algorithms with Machine Learning Models for Multiobjective Optimization in Epidemics Control
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    Chapter 32 Joint Price Optimization Across a Portfolio of Fashion E-Commerce Products
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    Chapter 33 Improving MOEA/D with Knowledge Discovery. Application to a Bi-objective Routing Problem
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    Chapter 34 The Prism-Net Search Space Representation for Multi-objective Building Spatial Design
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    Chapter 35 Selection Strategies for a Balanced Multi- or Many-Objective Molecular Optimization and Genetic Diversity: A Comparative Study
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    Chapter 36 A Multi-objective Evolutionary Framework for Identifying Dengue Stage-Specific Differentially Co-expressed and Functionally Enriched Gene Modules
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    Chapter 37 Real-World Airline Crew Pairing Optimization: Customized Genetic Algorithm Versus Column Generation Method
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    Chapter 38 Multiobjective Optimization of Evolutionary Neural Networks for Animal Trade Movements Prediction
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    Chapter 39 Transfer of Multi-objectively Tuned CMA-ES Parameters to a Vehicle Dynamics Problem
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    Chapter 40 Preference-Based Nonlinear Normalization for Multiobjective Optimization
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    Chapter 41 Incorporating Preference Information Interactively in NSGA-III by the Adaptation of Reference Vectors
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    Chapter 42 A Systematic Way of Structuring Real-World Multiobjective Optimization Problems
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    Chapter 43 IK-EMOViz: An Interactive Knowledge-Based Evolutionary Multi-objective Optimization Framework
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    Chapter 44 An Interactive Decision Tree-Based Evolutionary Multi-objective Algorithm
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Title
Evolutionary Multi-Criterion Optimization
Published by
Springer Nature Switzerland, April 2023
DOI 10.1007/978-3-031-27250-9
ISBNs
978-3-03-127249-3, 978-3-03-127250-9
Editors

Emmerich, Michael, Deutz, André, Wang, Hao, Kononova, Anna V., Naujoks, Boris, Li, Ke, Miettinen, Kaisa, Yevseyeva, Iryna

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